HuR-Associated Biomarkers

ABSTRACT

The present invention relates to methods of identifying gene targets, including methods of using ribonucleoprotein (RNP) immunoprecipitation-microarrays to identify cancer gene targets, such as subsets of RNP-associated mRNAs in breast cancer cell lines. Also presented, are ribonucleotide binding protein-associated biomarkers, panels or sets of ribonucleotide binding protein-associated biomarkers, methods and compositions comprising ribonucleotide-binding protein, associated nucleotides, nucleotide arrays, and kits to facilitate the diagnosis of and monitoring the disease status or progression of treatment of breast cancers, including drug-resistant breast cancers.

CROSS-REFERENCE TO RELATED APPLICATIONS

The pending application claims priority claims under 35 U.S.C. §119(e)to U.S. Provisional Patent Application No. 61/313,463, filed Mar. 12,2010, the disclosure of which is incorporated herein by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This disclosure was made with government support under contractW81XWH-07-1-0406 awarded by the Department of Defense. The U.S.Government has certain rights in the invention.

INCORPORATION BY REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISK

The sequence listing contained in the file “UMCO D604U1(09UMC071)_ST25.txt” modified on Mar. 9, 2011, having a file size of4,724 bytes, is incorporated by reference in its entirety herein.

FIELD

Presented are methods of identifying gene targets, including methods ofusing ribonucleoprotein (RNP) immunoprecipitation-microarrays toidentify cancer gene targets, such as subsets of RNP-associated mRNAs inbreast cancer cell lines. Also presented, are ribonucleotide bindingprotein-associated biomarkers, panels or sets of ribonucleotide bindingprotein-associated biomarkers, methods and compositions comprisingribonucleotide-binding protein-associated nucleotides, nucleotidearrays, and kits to facilitate the diagnosis of and monitoring thedisease status or progression of treatment of breast cancers, includingdrug-resistant breast cancers.

BACKGROUND

Over the past decade, array technologies have provided several new meansfor profiling global changes in gene expression. The power of DNAmicroarrays is perhaps best illustrated in the way it has been used todifferentiate treatment responses in patient populations. Individualizedand targeted therapy for several tumors, based upon underlyingdifferences at the molecular level among gene expression profiles, isbeginning to replace traditional morphological-based treatment models[Dietel M et al., Arch 2006, 448(6):744-755; Mischel P S et al., Nat RevNeurosci 2004, 5(10):782-792; N Engl J Med 2006, 355(26):2783-2785].Genome-wide microarray analyses, however, are inherently flawed sincethey globally profile the steady-state levels of mRNAs, referred to asthe transcriptome. Cellular protein expression levels, however, do notdirectly correlate with steady-state levels of mRNAs. It is wellaccepted that there is a poor correlation between steady-state RNAlevels and protein levels. This discordance has been attributed topost-transcriptional control mechanisms affecting mRNA stability andtranslation. Steady-state mRNA levels of genes controlled partially ortotally at this level may be misleading. Gygi and colleagues, forexample, have shown that correlations between mRNA and protein levelscould not be predicted from information about mRNA steady-state levelsalone [Mol Cell Biol 1999, 19(3):1720-1730]. They observed that somegenes had the same mRNA levels, but protein levels varied more than20-fold. Conversely, some proteins had equal expression levels, buttheir respective mRNA levels varied by more than 30-fold. They concludedthat “transcript levels provide little predictive value with respect tothe extent of protein expression” [Gygi SP et al., Mol Cell Biol 1999,19(3):1720-1730]. Idekar and colleagues have also described similarresults for the galactose gene [Ideker T et al., Science 2001,292(5518):929-934].

Although our understanding of transcriptional gene regulation isadvanced, post-transcriptional gene regulation remains largelyunexplored. It is becoming clear, however, that this is an importantmode of gene regulation, particularly for proinflammatory genes. Thesegenes appear to be regulated at a post-transcriptional level by RNAbinding proteins (RBPs), which interact with AU-rich elements (AREs) inthe 3′ untranslated region (UTR) of mRNAs. Approximately 3,000 humangenes contain AREs, representing 8% of the human genome [Khabar K S etal., Genomics 2005, 85(2):165-175]. Many of the genes which possess AREsare involved in areas of transient biological responses including cellgrowth and differentiation, immune responses, signal transduction,transcriptional and translational control, hematopoiesis, apoptosis,nutrient transport, and metabolism [Khabar K S et al., Genomics 2005,85(2):165-175; Khabar K S, J Interferon Cytokine Res 2005, 25(1):1-10].

New methods have revealed the identification of in vivo mRNA targets ofdifferent RBPs on a global scale. The ribonomic approach involvesseveral steps, including immunoprecipitation of ribonuclear particlecomplexes (RNPs) with antibodies directed against different RBPs,extraction of mRNAs, and hybridization of the mRNAs to microarrays[Intine R V et al., Mol Cell 2003, 12(5):1301-1307; Tenenbaum et al.,Proc Natl Acad Sci USA 2000, 97(26):14085-14090; Tenenbaum S A et al.,Methods 2002, 26(2):191-198]. This “RIP-Chip” approach enablesinvestigators to identify groups of post-transcriptionally regulatedmRNAs, which are coordinately controlled by RBPs during variousbiological processes. A new model has been developed which states thatRBPs coordinately regulate the expression of biologically relatedmolecules [Keene J D, Nat Genet 2003, 33(2):111-112; Keene J D,Tenenbaum S A, Mol Cell 2002, 9(6):1161-1167]. The “post-transcriptionaloperon hypothesis” is being confirmed in many different laboratories,broadening our understanding of post-transcriptional regulation asputative operons are characterized at a molecular level [Intine R V etal., Mol Cell 2003, 12(5):1301-1307; Gerber A P et al., PLoS Biol 2004,2(3):E79; Grigull J et al., Mol Cell Biol 2004, 24(12):5534-5547;Hieronymus H, Silver P A, Nat Genet 2003, 33(2):155-161; Hieronymus H etal., Genes Dev 2004, 18(21):2652-2662; Rajasekhar V K, Holland E C,Oncogene 2004, 23(18):3248-3264].

HuR is a RBP that binds to AREs of many proto-oncogenes and labilemRNAs. It has emerged as a key regulatory factor which stabilizes andtranslationally enhances its targets mRNAs, and affects their transportfrom the nucleus to the cytoplasm [Atasoy U et al., J Cell Sci 1998, 111(Pt 21):3145-3156; Fan X C, Steitz J A, Embo J 1998, 17(12):3448-3460;Ma W J et al., J Biol Chem 1996, 271(14):8144-8151]. HuR belongs to theELAV (embryonic lethal abnormal vision) family found in mammalian cellscontaining four members: HuR, HuB, HuC, and HuD. HuR is the onlyubiquitously-expressed member. The others are found primarily in thecentral nervous system and gonadal tissue [Atasoy U et al., J Cell Sci1998, 111 (Pt 21):3145-3156]. Many HuR targets are cytokines,chemokines, and other early-response genes [Meisner N C et al.,Chembiochem 2004, 5(10):1432-1447; Brennan C M, Steitz J A, Cell MolLife Sci 2001, 58(2):266-277].

HuR has been demonstrated to control expression of genes in multipleareas of malignant transformation, one of the hallmarks of cancer firstdescribed by Hanahan and Weinberg [Cell 2000, 100(1):57-70]. Subsequentstudies have suggested that HuR plays a role as a tumor maintenancegene, permissive for malignant transformation, tumor growth, and perhapsmetastasis [Lopez de Silanes I et al., RNA Biol 2005, 2(1):11-13]. HuRhas also been described in the literature as controlling the expressionof many cancer-relevant genes, including those that encode proteins suchas Prothymosin-α, Bcl-2, Mcl-1, SirT1, TGF-β, MMP-9, MTC-1, uPA, VEGF-α,HIF1-α and cyclins A, B1 and D1 [Abdelmohsen K et al., Cell Cycle 2007,6(11):1288-1292; Abdelmohsen K et al., Mol Cell 2007, 25(4):543-557; LalA et al., Embo J 2005, 24(10):1852-1862; Lal A et al., EMBO J 2004,23(15):3092-3102; Levy A P, Trends Cardiovasc Med 1998, 8(6):246-250;Lopez de Silanes I et al., Proc Natl Acad Sci USA 2004,101(9):2987-2992; Nabors L B et al., Cancer Res 2001, 61(5):2154-2161;Sheflin L G et al., Biochem Biophys Res Commun 2004, 322(2):644-651;Tran H et al., Mol Cell Biol 2003, 23(20):7177-7188; Wang W et al., EMBOJ 2000, 19(10):2340-2350; Wang W et al., Mol Cell Biol 2001,21(17):5889-5898]. Increased levels of HuR have been associated withmore aggressive breast cancers, which have a more serious progressionand outcome [Denkert C et al., Clin Cancer Res 2004, 10(16):5580-5586;Heinonen M et al., Cancer Res 2005, 65(6):2157-2161; Heinonen M et al.,Clin Cancer Res 2007, 13(23):6959-6963].

HuR has also been described as post-transcriptionally regulating theexpression of many breast cancer-relevant genes, including those thatencode Glut-1, ERα, COX-2, IL-8, Cyclin E1, and BRCA-1 [Denkert C etal., Clin Cancer Res 2004, 10(16):5580-5586, Gantt K R et al., J CellBiochem 2006, 99(2):565-574; Guo X, Hartley R S, Cancer Res 2006,66(16):7948-7956; Kang S S et al., Jpn J Cancer Res 2002,93(10):1123-1128; Pryzbylkowski P et al., Breast Cancer Res Treat 2008,111(1):15-25; Saunus J M et al., Cancer Res 2008, 68(22):9469-9478;Suswam E A et al., Int J Cancer 2005, 113(6):911-919]. HuR RIP-Chipanalysis has recently identified Thrombospondin 1 as a key HuR target inthe MCT-1 transformed estrogen receptor positive (ER+) cell line, MCF-7[Mazan-Mamczarz K et al., Oncogene 2008, 27: 6151-6163]. Itsinteractions, however, are complex, and at times, HuR may interact withmiRNAs, such as Let-7, to translationally suppress the expression ofC-MYC mRNAs [Kim H H et al., Genes & Dev 2009, 23: 1743-1748].

In view of the emerging role that HuR appears to have in influencing theexpression of many cancer-relevant genes, we were interested indetermining whether HuR was involved in coordinately regulating theexpression of breast cancer genes in ER+ and ER− breast cancers. Weperformed a HuR RIP-Chip analysis on MDA-MB-231 (ER−) and MCF-7 (ER+)cell lines to identify cancer-relevant genes not known to be regulatedby HuR, and to identify potential novel breast cancer targets. Ourstudies indicated that HuR was associated with unique subsets of mRNAsin each cell line, as well as a subset of HuR-associated mRNA targetscommon to both. We chose two cancer-associated genes, CD9 and CALMODULIN2 (CALM2), highly expressed in both cell lines, and functionallyvalidated the role of HuR in regulating their expression. Unexpectedly,HuR differentially regulated the same target, CD9, in both cell lines inan opposite manner. Moreover, we found presumptive differentialregulation of CALM2 by HuR, as HuR interacted only with CALM2 mRNA, butnot with family members CALM1 and CALM3 mRNAs. We discovered that HuRinteracts with many breast cancer-relevant genes, not previously knownto be controlled by HuR, and target genes which have not been shown tobe cancer-related. This latter category may represent novel cancer genesdiscovered by HuR RIP-Chip analysis.

Clinical tests based on molecular analysis of key nucleotide or proteinbiomarkers have been widely used to study pathogenic disease processesand evaluate responses to drug therapy procedures. Biomarkers have alsobeen used to predict susceptibility of an individual to specificdiseases and to predict responses to drug treatments. Approaches basedon the detection and statistical analysis of multiple biomarkers greatlyfacilitate the identification of key factors involved in the developmentof complex disease states, and their treatment.

While many established testing schemes rely upon methods to measurechanges in specific nucleotide, protein, or metabolite levels, very fewcan match the power of nucleotide microarrays to facilitate theevaluation of biomarker analyses in parallel, or the ability of massspectrometry to identify large numbers of proteins or other componentsin complex sample mixtures. Methods of using microarray analysis tomonitor the level of mRNAs within a cell, however, often miss geneswhich are regulated primarily at the level of mRNA stability andtranslation, due to the poor correlation between steady-state mRNAlevels and protein products. Therefore, there is a need to provide a newand improved method to identify, en masse, novel RBP targets associatedwith cancer genes in vivo from representative cell lines and clinicalsamples, using methods which facilitate the evaluation of a wide varietyof biomarkers.

SUMMARY

Provided are methods to identify novel biomarkers, which can be used inscreening or diagnostic tests. The method may also identify noveltargets for new cancer therapeutics. When applied to breast cancer, themethod may lead to the identification of genes responsible for differentsubtypes of breast cancer, such as genes that mediate tamoxifenresistance, which in turn, may lead to the development of noveltherapeutics to overcome tamoxifen resistance.

Provided are methods for identifying a ribonucleotide bindingprotein-associated biomarker, comprising the steps of (a) preparing apolysomal lysate from a cultured cell line, non-cultured cells, or solidtissue; (b) preparing a first immunoprecipitation complex from saidpolysomal lysate using an antibody directed against a ribonucleotidebinding protein and a second immunoprecipitation complex from saidpolysomal lysate using an antibody which is an isotype of the antibodydirected against the ribonucleotide binding protein; (c) extracting RNAfrom said immunoprecipitation complexes; (d) amplifying said RNA to formcDNA; (e) labeling said cDNA; (e) hybridizing said labeled cDNA to oneor more nucleic acids immobilized on a microarray; and (f) determiningthe ratio of labeled cDNA prepared from the first immunoprecipitationcomplex to that obtained from the second immunoprecipitation complexbound to the one or more one or more nucleic acids immobilized on amicroarray.

Also provided are ribonucleotide binding protein-associated biomarkers,which may be identified by any of the methods noted above, wherein theratio of labeled cDNA prepared from the first immunoprecipitationcomplex to that obtained from the second immunoprecipitation complexbound to the one or more nucleic acids immobilized on a microarray isgreater than 4, 6, 8, or 10.

Also provided are HuR-associated biomarkers. In some cases, thebiomarkers are selected from the group consisting of CALM2, CD9, SRRM1,CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, wherein the level ofexpression is over- or under-expressed in a breast cancer samplecompared to a standard level of expression of the same biomarker in anon-cancerous sample.

In addition, a panel or set of biomarkers is provided comprising atleast one HuR-associated biomarker selected from the group consisting ofCALM2, CD9, SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1,wherein the level of expression is over- or under-expressed in a breastcancer sample compared to a standard level of expression of the samebiomarker in a non-cancerous sample.

Also provided are methods of aiding in the identification of subjects atrisk to develop breast cancer, aiding in the diagnosis of breast cancer,aiding in monitoring of disease status of breast cancer, aiding in themonitoring of breast cancer therapy, aiding in monitoring of breastcancer therapy safety, and aiding in the determination of theeffectiveness of a chemotherapy agent in treating breast cancer.

A better understanding of the disclosed methods of identifyingbiomarkers, sets of biomarkers, and methods of using the sets tofacilitate the diagnosis of, or to monitor the disease status orprogression of a cancer, can be obtained from the following detaileddescriptions and accompanying drawings, which set forth illustrativeexamples indicative of the various ways in which the principals of thedisclosure may be employed.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the advantages of this disclosure aremore readily appreciated as the same become better understood byreference to the following detailed description, when taken inconjunction with the accompanying drawings, wherein:

FIG. 1 sets forth data illustrating Immunoprecipitation and RIP inMB-231 and MCF-7 breast cancer cells. Immunoprecipitations wereperformed from MB-231 or MCF-7 cell lysates using anti-HuR monoclonalantibody (3A2) and IgG1 isotype control. Panel 1A. IP Western of HuRrevealed expected size band as detected by 3A2. The subpanel on theright reveals amounts of HuR in lysates used from both cell lines. Panel1B. Verification by quantitative RT-PCR showed fifteen and eleven foldenrichments of B-ACTIN, a known HuR target, in the 3A2 IPs from MB231and MCF-7, respectively. All ΔΔ C_(T) values were normalized to GAPDH.Experiments were done in duplicate (n=2).

FIG. 2 sets forth data illustrating that the HuR RIP-CHIP identifiesdistinct genetic profiles in ER+ and ER− breast cancer cells. HuRimmunoprecipitations were performed from MB-231 or MCF-7 cell lysatesusing HuR antibody and IgG1 isotype control hybridized to IlluminaSentrix arrays (47,000 genes). Control signals were subtracted. Resultsrepresent cumulative data from 12 different arrays. Experiments weredone in triplicate (n=3) for each cell line with matching controls.Scales are log 2.

FIG. 3 sets forth data illustrating the GO Classification of genes foundby RIP CHIP of potential HuR targets and their relationship to theAcquired Capabilities of Cancer Model. Panel 3A. Differentiallyexpressed genes which are more represented in the Biological Processes(BP) GO category than expected. Panel 3B. Original representationshowing subsets of transcripts found to be targets of association withHuR (normal type). New transcripts found in this study with RIP-Chip(bold type). Enhanced expression upon binding to HuR influences severalof the acquired capabilities of cancer cells described previously[Hanahan D, Weinberg R A, Cell 2000, 100(1):57-70; Lopez de Silanes I,Lal A, Gorospe M, RNA Biol 2005, 2(1):11-13].

FIG. 4 sets forth data illustrating validation of target CALM2 and CD9mRNAs by quantitative RT-PCR. Quantitative RT-PCR using RNA extractedfrom cell lysates of RIP CHIP analysis confirmed results identifyingCALM2 mRNA (A) and CD9 mRNA (B) as HuR targets. Change in geneexpression is represented as fold increase in HuR immunoprecipitation ascompared to IgG1. GAPDH mRNA was used as an endogenous control. Errorbars represent SEM. p value is <0.005. Experiments were done intriplicate (n=3).

FIG. 5 sets forth data illustrating biotin pull-down assays of CD9 andCALM2. Panel 5A. Scheme of Coding region (CR) and 3′UTR fragments forbiotin pull-down assay. The sequences were obtained from Entrez database. CR and 3′UTR fragments selected for amplification by PCR are asnoted. Panel 5B. 1% agarose gel electrophoresis showing PCR amplifiedproducts of the coding regions and 3′UTR's for CD9 (442 bp and 432 bp,respectively) and CALM2 (443 bp and 610 bp, respectively). Panel 5C.Biotin pull down assay using lysates prepared from MB-231 cells. Thebinding of HuR to biotinylated 3′UTR transcripts from both CD9 and CALM2mRNAs was specific. HuR did not bind a biotinylated control (GAPDH3′UTR) and did not bind to biotinylated transcripts spanning the CR ofCD9 or CALM2. Experiments were done in duplicate (n=2).

FIG. 6 sets forth data illustrating that HuR differentially regulatesCD9 and CALM2 in MB-231. Panel 6A. Epitope HA tagged HuR is overexpressed by 142% and 138% respectively, in stably transfected clones4E1 and 5F1, as compared to empty vector (EV) control clone 2C7. Panel6B. HuR knock down using lentiviral short hairpin (sh) RNA H760 resultsin a 94% reduction in steady state levels of protein in clone A7(LL=lentilox control). Panel 6C. HuR over expression results in a 40%reduction in CD9 protein levels as assayed by Western analysis; however,HuR knock down using lentiviral shRNA results in an increase from 100%to 228% of CD9 levels. Panel 6D. Over expression of HuR decreases CD9mRNA levels but not CALM2 expression. Analysis of steady state CD9 andCALM2 mRNA levels by quantitative RT-PCR reveals significant decreasesin CD9 mRNA levels, whereas CALM2 levels are unaffected. Although CALM2expression appears greater, the change is not significant. Panel 6E.Knocking down HuR levels by shRNA in MB-231 cells shows significantincreases in CD9 and CALM2 mRNA levels by quantitative RT-PCR. Decreasedlevels of HuR mRNA validate HuR shRNA knock down. Panel 6F. Graphshowing the effects of HuR on the expression of CD9 mRNA. HuR overexpression results in decreases in both mRNA and protein levels, thoughthe decreases are greater in RNA. Whereas, HuR knock down by shRNAresults in significant increases at both the mRNA and protein levels,with greater change at transcript levels. The dashed line representslevels in control cells. Error bars represent SEM. p value is <0.005;N.S.=not statistically significant; and *=statistically significant. Allexperiments were done in triplicate (n=3).

FIG. 7 sets forth data illustrating the effects of overexpressing orreducing HuR on CD9 and CALM2 expression in MCF-7 cells. Panel 7A.Western analysis of HuR over expression in heterogenous population ofcells reveals approximately 10% over expression. Panel 7B. LentiviralHuR shRNA efficiently knocks down HuR protein by over 90%. Panel 7C. HuRover expression and under expression results in small changes in CD9protein levels in MCF-7 cells. Panel 7D. Levels of both CD9 and CALM2mRNAs are unchanged in cells which over express HuR; whereas lentiviralknock down of HuR in MCF-7 cells results in decreases in steady-statemRNA levels (Panel 7E). The graph in Panel 7F shows minimal changes inCD9 mRNA and protein levels for in HuR over expressing MCF-7 cells. TheCD9 mRNA levels, however, are more affected in HuR knock down. P valueis <0.005; N.S.=not statistically significant; and *=statisticallysignificant.

FIG. 8 sets forth data illustrating that total cellular levels of HuRare similar in MB-231 and MCF-7 cells. Nuclear and cytoplasmicseparation was performed to measure levels of HuR in differentcompartments of MB-231 and MCF-7 cells. Total cellular HuR levels werevery similar, whereas there was a small (10%) increase in HuRcytoplasmic levels in MB-231 cells as compared to MCF-7. Absence oftubulin staining demonstrates integrity of isolation as there should notbe tubulin in the nuclear fraction. Bands were measured by densitometryand normalized to tubulin controls. (T=total cellular lysate;C=cytoplasmic lysate, N=nuclear lysate).

FIG. 9 sets forth data illustrating the relative baseline values ofCALM1, CALM2, CALM3, and CD-9 mRNAs in ER+ and ER− cells. QuantitativeRT-PCR performed on mRNA extracted from cell lysates showing relativelevels of CALM1, CALM2, CALM3, and CD-9 mRNAs in MB231 and MCF-7 breastcancer cells. All values were normalized to GAPDH mRNA. All experimentswere done in triplicate (n=3) except for CALM3 (n=2).

Abbreviations and their corresponding meanings include: aa or AA=aminoacid; ER=estrogen receptor; mg=milligram(s); ml or mL=milliliter(s);mm=millimeter(s); mM=millimolar; nmol=nanomole(s); ORF=open readingframe; PCR=polymerase chain reaction; pmol=picomole(s); ppm=parts permillion; RT=reverse transcriptase; RT=room temperature; SDS-PAGE=sodiumdodecyl sulfate-polyacrylamide gel electrophoresis; U=units; ug,μg=micro gram(s); ul, μl=micro liter(s); and uM, μM micromolar; Estrogenreceptor negative (ER−), estrogen receptor positive (ER+), RNAimmunoprecipitation (RIP), RNA immunoprecipitation applied tomicroarrays (RIP-Chip), 3′ untranslated region (3′ UTR), ELAV1(embryonic lethal abnormal vision 1).

The term “biomarker” in the context of the present inventionencompasses, without limitation, proteins, nucleic acids, andmetabolites, together with their polymorphisms, mutations, variants,modifications, subunits, fragments, protein-ligand complexes, anddegradation products, protein-ligand complexes, elements, relatedmetabolites, and other analytes or sample-derived measures. Biomarkerscan also include mutated proteins or mutated nucleic acids. Biomarkersalso encompass non-blood borne factors or non-analyte physiologicalmarkers of health status, such as “clinical parameters” defined herein,as well as “traditional laboratory risk factors”, also defined herein.Biomarkers also include any calculated indices created mathematically orcombinations of any one or more of the foregoing measurements, includingtemporal trends and differences.

The term “analyte” as used herein can mean any substance to be measuredand can encompass electrolytes and elements, such as calcium.

The term “set” means a collection of objects, which may include zero,one, or two or more objects. A set of biomarkers, for example, includesa set of one biomarker, or more commonly, a set of two or morebiomarkers.

DETAILED DESCRIPTION

Provided are methods to identify novel biomarkers, which can be used forscreening and diagnostic testing. The method may also identify noveltargets for new cancer therapeutics. When applied to breast cancertissues, the method may lead to the identification of genes responsiblefor different subtypes of breast cancer, such as genes that mediatetamoxifen resistance. Identification and characterization of similargenes may lead to the development of novel therapeutics that canovercome drug resistant forms of these and other types of cancer.

Presented is a method called Ribonomic Analysis, or RNAimmunoprecipitations applied to microarrays (RIP-on-Chip), to identifyen masse, in vivo targets of RBPs from cultured cell lines and solidtissues. RIP Chip technology can be used, for example, to identifycellular targets of HuR within cultured cell lines. The RIP-on-Chip wasused to identify distinct subsets of HuR associated mRNAs in MDA MB231and MCF-7 breast cancer cell lines. The role of HuR in triple negativebreast cancer was also investigated by overexpressing HuR in MB231cells, which results in accelerated growth. HuR pull down experimentsdemonstrated that the RIP-on-Chip technology can be used to identifyknown cancer targets, and distinct subsets of relevant cancer genes,plus novel cancer targets, suitable for detailed characterization.

One aspect of the invention relates to an HuR-associated biomarkerselected from the group consisting of CALM2, CD9, SRRM1, CCN1, DAZAP2,ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, wherein the level of expression isover- or under-expressed in a breast cancer sample compared to astandard level of expression of the same biomarker in a non-canceroussample.

Another aspect of the invention relates to a set of HuR-associatedbiomarkers comprising at least one biomarker selected from the groupconsisting of CALM2, CD9, SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1,MMD and TMCO1, wherein the level of expression at least one biomarker isover- or under-expressed in a breast cancer sample compared to astandard level of expression of the same biomarker in a non-canceroussample.

A sample obtained from a subject, without being limiting, can includeisolated cells, tissue samples, or bodily fluids, including blood,plasma, serum, sputum, urine, stools, tears, mucus, hair, skin, or otherfluids secreted or excreted from various organs or specialized cells.Samples are typically obtained from humans, but may include tissuesobtained from non-human primates or rodents. Samples may also includesections of tissues taken from biopsy or autopsy samples, explants andprimary or transformed cell cultures derived from subject tissues. Asample can be compared on a cellular basis, or on a volume basis forfluids, or normalized to the amount of mRNA, protein, or othermacromolecule or chemical in an extract obtained from a sample ofdispersed cells, tissue, or biological fluid.

The standard level of expression, or a range of acceptable levels, of abiomarker can be determined by a variety of methods. For example, areference range can be established by evaluating the distribution ofsaid marker among non-cancerous samples obtained from a population ofhealthy subjects in conjunction with the corresponding distribution ofcancerous samples. For biomarkers, values which exceed a criticalthreshold are of particular interest, so that only values outside thereference range in a particular direction are of use. The optimalthreshold can be determined with respect to the most desired propertiesof the biomarker (e.g., sensitivity, specificity, reliability) whichdepends on the intended use (e.g., diagnostic or screening). Suchmethods for determining the optimal threshold include, receiveroperating characteristic curves, Bayesian classifiers, or otherdecision-theoretic methods. In one aspect of the invention, it ismeasured as the median expression level of the biomarker in anon-cancerous sample obtained from one or more samples obtained from apopulation of healthy subjects. In another aspect of the invention, thestandard level of expression is the median expression level of thebiomarker in a non-cancerous sample obtained from one or more samplesobtained from a subject having breast cancer.

Levels of protein expression may be determined by a number oftechniques, as are well known to one of skill in the art. Examplesinclude western blots, immunohistochemical staining andimmunolocalization, immunofluorescence, enzyme-linked immunosorbentassay (ELISA), immunoprecipitation assays, agglutination reactions,radioimmunoassay, flow cytometry and equilibrium dialysis. These methodsgenerally depend upon a reagent specific for identification of HuRassociated-biomarkers. The reagent is may be an antibody and maycomprise monoclonal or polyclonal antibodies. Fragments and derivatizedantibodies may also be utilized, to include without limitation Fabfragments, ScFv, single domain antibodies, nanoantibodies, heavy chainantibodies etc which retain binding function. Any detection method maybe employed in accordance with the invention. The nature of the reagentis not limited except, that it must be capable of specificallyidentifying HuR associated-biomarkers.

Suitable methods for determining HuR associated-biomarkers expression atthe RNA level are well known in the art. Methods employing nucleic acidprobe hybridization to the HuR associated-biomarkers transcript may beemployed for measuring the presence and/or level of HuRassociated-biomarkers mRNA. Such methods include use of nucleic acidprobe arrays (microarray technology) and Northern blots. Advances ingenomic technologies now permit the simultaneous analysis of thousandsof genes, although many are based on the same concept of specificprobe-target hybridization.

Sequencing-based methods are an alternative. These methods started withthe use of expressed sequence tags (ESTs), and now include methods basedon short tags, such as serial analysis of gene expression (SAGE) andmassively parallel signature sequencing (MPSS). Differential displaytechniques provide yet another means of analyzing gene expression; thisfamily of techniques is based on random amplification of cDNA fragmentsgenerated by restriction digestion, and bands that differ between twotissues identify cDNAs of interest.

In one aspect, the levels of HuR associated-biomarkers gene expressionare determined using reverse transcriptase polymerase chain reaction(RT-PCR). RT-PCR is a well known technique in the art which relies uponthe enzyme reverse transcriptase to reverse transcribe mRNA to formcDNA, which can then be amplified in a standard PCR reaction. Protocolsand kits for carrying out RT-PCR are extremely well known to those ofskill in the art and are commercially available.

In another aspect, the RT-PCR is carried out in real time and in aquantitative manner. Real time quantitative RT-PCR has been thoroughlydescribed in the literature (see Gibson et al for an early example ofthe technique) and a variety of techniques are possible. Examplesinclude use of Taqman, Molecular Beacons, LightCycler (Roche), Scorpionand Amplifluour systems. All of these systems are commercially availableand well characterised, and may allow multiplexing (that is, thedetermination of expression of multiple genes in a single sample).

These techniques produce a fluorescent read-out that can be continuouslymonitored. Real-time techniques are advantageous because they keep thereaction in a “single tube”. This means there is no need for downstreamanalysis in order to obtain results, leading to more rapidly obtainedresults. Furthermore, keeping the reaction in a “single tube”environment reduces the risk of cross contamination and allows aquantitative output from the methods of the disclosure.

Variants on the basic PCR technique may also be used such as nested PCR,equivalents may also be included within the scope of the invention.Examples include isothermal amplification techniques such as NASBA, 3SR,TMA and triamplification, all of which are well known in the art andcommercially available. Other suitable amplification methods include theligase chain reaction (LCR) [Barringer et al, Gene 1990, 89(1):117-122],selective amplification of target polynucleotide sequences [U.S. Pat.No. 6,410,276], consensus sequence primed polymerase chain reaction[U.S. Pat. No 4,437,975], arbitrarily primed polymerase chain reaction[WO 90/06995] and nick displacement amplification [WO 2004/067726].

The panel or set comprises at least one, two, three, four, etc of theHuR associated-biomarkers genes listed, up to all genes. Allpermutations and combinations of the genes listed above are contemplatedfor gene panels.

For larger panels, use of microarrays may be used in determining levelsof HuR associated-biomarkers indirectly by looking at expression ofother genes, comprising probes immobilized on a solid supporthybridizing with transcripts or parts thereof of at least one geneselected from those listed. For these groups of genes the changes inexpression are calculated to be highly significant (p<0.01). The probesmay be immobilized on a solid support hybridizing with transcripts orparts thereof of at least one, two, three, four, etc of the genes listedabove, up to all of the genes. All permutations and combinations of thegenes listed above are contemplated within the scope of the presentinvention, for the purposes of providing a microarray. Microarrays andtheir means of manufacture are well known and can be manufactured toorder by commercial entities, such as Agilent and Affymetrix.

The elements of probe selection and design are common to the productionof all arrays, regardless of their intended application and as suchwould be well known to one of skill in the art. Strategies to optimizeprobe hybridization, for example, may be included in the process ofprobe selection. Hybridization under particular pH, salt, andtemperature conditions can be optimized by taking into account meltingtemperatures and using empirical rules that correlate with desiredhybridization behaviors.

To facilitate comparisons, the level of expression in a biomarker inbreast cancer sample, is measured against a similar, if not identical,amount of sample used to determine the standard level of expression thebiomarker in a non-cancerous sample obtained from a population ofsubjects, or from a non-cancerous sample obtained from a subject havingbreast cancer. The standard can be measured, if desired, from the samesubject from whom the breast cancer sample was obtained.

In one aspect, the ratio of expression of at least one biomarkerexpressed in the breast cancer sample compared to the non-canceroussample is less than ½ or greater than 2. Higher and lower thresholds canbe used, such as less than ¼ and greater than 4, less than ⅛ and greaterthan 8, less than 1/16 and greater than 16, etc., to facilitatestatistical analysis, where adequate to optimal signal-to-noise ratiosare used for each of the biomarkers in the set of biomarkers used to aidin the diagnosis of, or to monitor the disease status or progression of,breast cancer in a subject.

In one aspect of the invention, the breast cancer is an estrogenreceptor positive breast cancer. In another aspect of the invention, thebreast cancer is an estrogen receptor negative breast cancer.

In one aspect of the invention, at least one of said biomarkers is anmRNA. In another aspect of the invention, at least one of saidbiomarkers is a polypeptide. In another aspect of the invention, atleast one of said biomarkers is post-transcriptionally regulated. Theset of biomarkers may include biomarkers that are all based on mRNAs, orbiomarkers that are all based on polypeptides. The set may alsoencompass a mix of both mRNA- and polypeptide-based biomarkers.

In one aspect, the set of biomarkers may further comprise at least onebiomarker selected from the group consisting of Prothymosin-α, Bcl-2,Mcl-1, SirT1, TGF-b, MMP-9, MTC-1, μPA, VEGF-α, HIF1-α and cyclins A1(CCNA1), B1 and D1.

In another aspect, the set of biomarkers may further comprise at leastone biomarker selected from the group consisting of Glut-1, ERα, COX-2,IL-8, Cyclin E1, BRCA-1 and Thrombospondin 1.

In another aspect, the set of biomarkers may further comprise at leastone biomarker selected from the group consisting of CD9, PTMA, UBE2E2,CCNI, CKLF, SRRM1, STK4, FKBP1A, PMP22, CALM2, MMD, CSDA, CHIC2, DAZAP2,ZNF22, ATP1B1, TRAM1, ENY2, ALKBH5, RAP2A, TMCO1, and ARL6IP1.

In another aspect, the set of biomarkers may further comprise at leastone biomarker selected from the group consisting of ACTB, SMNDC1, MAL2,CALM2, CDK2AP1, hCG_(—)1781062, JUND, ARL6IP1, PTMA, ATP6V1G1, ACTB,HMGB1, BUB3, PJA2, LOC203547, NPM1, MATR3, TMC01, CXCR7, ZFP36L1, SFRS2,TMSL3, PLOD2, PPP6C, EIF4A2, RPS6KB1, HSPA1A, TIMEM59, FOXA1, PEX11B,MYB, CD9, ZNF14, ITGB1, PARD6B, LOC441087, SRRM1, SNX16, PUM1, MORF4L1,TFDP1, MMD, GCA, CISD2, C4orf34, DAZAP2, G3BP1, C21orf55, NCOA3, ATP1B1,SFPQ, PRKAR1A, YBX1, HIST1H3E, CCNI, CSTB, C15orf51, YWHAZ, PRIM2,SLC7A1, C15orf15, PCBP2, ROD1, SPINT2, CALMG, and YTHDC1.

One aspect is directed to a kit for measuring the level of expression ofa set of HuR-associated biomarkers comprising at least one biomarkerselected from the group consisting of CALM2, CD9, SRRM1, CCN1, DAZAP2,ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, wherein the level of expression atleast one biomarker is over- or under-expressed in a breast cancersample compared to a standard level of expression of the same biomarkerin a non-cancerous sample.

Kits for use in diagnostic, research, and therapeutic applications mayinclude any or all of the following items: assay reagents, buffers,hybridization probes or primers, biomarker-specific nucleic acids orantibodies, antisense polynucleotides, siRNAs, shRNAs, ribozymes, smallmolecule inhibitors of cancer-associated enzymes or nucleic acids,reaction tubes, etc. Kits intended for therapeutic use may includesterile saline or other pharmaceutically-acceptable solutions. Kits mayalso include instructional materials, which may be written or encoded onelectronic storage media. A wide variety of kits and components may beprepared according to the present invention, depending on its intendeduse. Kits of the invention typically be used to evaluate a plurality ofgenes or gene products which are selected based on statisticallysignificant parameters relating to the diagnosis, diseases status, orprogression of a disease of interest.

The kit may also include reagents necessary for a nucleic acidamplification step. Reagents may include, by way of example and notlimitation, amplification enzymes, probes, positive controlamplification templates, reaction buffers etc. For example, in the PCRmethod of amplification, possible reagents include a suitable polymerasesuch as Taq polymerase and appropriate PCR buffers, and in the TMAmethod the appropriate reagents include RNA polymerase and reversetranscriptase enzymes. All of these reagents are commercially availableand well known in the art.

The kit may further include components required for real time detectionof amplification products, such as fluorescent probes for example. Therelevant real-time technologies, and the reagents required for suchmethods, are well known in the art and are commercially available.Probes may need to be of sequence such that they can bind between PCRprimer sites on the nucleic acid molecule of interest that issubsequently detected in real-time. Other probes may be designed thatbind to a relevant portion of the relevant nucleic acid sequence.Suitable probes are accordingly included in a further aspect of the kitsof the invention. Kits for use in methods where recruitment to apromoter, or levels of histone acetylation are measured, may includesuitable components necessary for carrying out a chromatinimmunoprecipitation.

Once the level or activity of HuR associated-biomarkers has beendetermined, it is then possible to conclude which type of treatment issuitable or not. Accordingly, a suitable information sheet may beincorporated in the kit which allows the user of the kit to interpretthe results to thus decide on an appropriate course of treatment. Thesheet may take the form of written instructions, or a flow chart ordecision tree, for example.

One aspect is directed to a method for aiding in the diagnosis of breastcancer in a subject comprising: (a) obtaining a sample from saidsubject; (b) measuring the level of expression of a set ofHuR-associated biomarkers comprising at least one biomarker selectedfrom the group consisting of CALM2, CD9, SRRM1, CCN1, DAZAP2, ARL6IP1,PTMA, ATP1B1, MMD and TMCO1, in said sample obtained from the subject;and (c) comparing the level of expression of each biomarker in the setof HuR-associated biomarkers to the standard level of expression of thesame biomarker in a non-cancerous sample; wherein a significantdifference in the ratio of expression of at least one biomarker in theset aids in the diagnosis of breast cancer.

Another aspect of the invention is directed to a method for monitoringthe disease status or progression of breast cancer in a subjectcomprising: (a) obtaining a sample from said subject; (b) measuring thelevel of expression of a set of HuR-associated biomarkers comprising atleast one biomarker selected from the group consisting of CALM2, CD9,SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, in saidsample obtained from the subject; and (c) comparing the level ofexpression of each biomarker in the set of HuR-associated biomarkers tothe standard level of expression of the same biomarker in anon-cancerous sample; wherein a significant difference in the ratio ofexpression of at least one biomarker in the set aids in monitoring thedisease status or progression of breast cancer.

Another aspect of the invention is directed to a method for monitoringthe disease status of breast cancer in a subject comprising: (a)obtaining a sample from said subject; (b) measuring the level ofexpression of a set of HuR-associated biomarkers comprising at least onebiomarker selected from the group consisting of CALM2, CD9, SRRM1, CCN1,DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, in said sample obtainedfrom the subject; and (c) comparing the level of expression of eachbiomarker in the set to the standard level of expression of eachcorresponding biomarker in the set in a non-cancerous sample; wherein asignificant difference in the ratio of expression of at least onebiomarker in the set aids the disease status of breast cancer in asubject. It is appreciated that this method can be performed multipletimes on multiple samples and that the comparison of biomarker levelsfrom one time to the next can be important in determining the status ofthe disease. For instance, this method may be performed beforeanti-cancer treatment, during treatment and/or after treatment as ameans of measuring the response of the subject to the treatment. Inaddition, the method may be applied longitudinally to a subject withoutany anti-cancer treatment to monitor disease status.

In one aspect, the ratio of expression of at least one biomarkerexpressed in the breast cancer sample compared to the non-canceroussample is less than ½ or greater than 2. Higher and lower thresholds canbe used, such as less than ¼ and greater than 4, less than ⅛ and greaterthan 8, less than 1/16 and greater than 16, etc., to facilitate thestatistical analysis, where adequate to optimal signal-to-noise ratiosare used for each of the biomarkers in the set of biomarkers used to aidin the diagnosis or to monitor the disease status or progression ofbreast cancer in a subject.

Also provided is a method of identifying a ribonucleotide bindingprotein associated biomarker, comprising the steps of (a) preparing apolysomal lysate from a cultured cell line, non-cultured cells, or solidtissue; (b) preparing a first immunoprecipitation complex from saidpolysomal lysate using an antibody directed against a ribonucleotidebinding protein and a second immunoprecipitation complex from saidpolysomal lysate using an antibody which is an isotype control of theantibody directed against the ribonucleotide binding protein; (c)extracting RNA from said immunoprecipitation complexes; (d) amplifyingsaid RNA to form cDNA; (e) labeling said cDNA; (e) hybridizing saidlabeled cDNA to one or more nucleic acids immobilized on a microarray;and (f) determining the ratio of labeled cDNA prepared from the firstimmunoprecipitation complex to that obtained from the secondimmunoprecipitation complex bound to the one or more one or more nucleicacids immobilized on a microarray.

In this aspect, the biomarker is a cancer biomarker. The biomarker maybe a ribonucleotide binding protein-associated biomarker. The biomarkermay be a breast cancer biomarker, which may be estrogen receptorpositive, or estrogen receptor negative. Also provided areribonucleotide binding protein associated biomarkers which may beidentified by the method of noted above, wherein the ratio of labeledcDNA prepared from the first immunoprecipitation complex to thatobtained from the second immunoprecipitation complex bound to the one ormore nucleic acids immobilized on a microarray is at least greater than2. In other aspects, the ratio is at least greater than 4, the ratio isat least greater than 5, the ratio is at least greater than 6, the ratiois at least greater than 8, or the ratio is at least greater than 10.

While specific examples have been described in detail, it will beappreciated by those skilled in the art that various modifications andalternatives to those details could be developed in light of the overallteachings of the disclosure. Accordingly, the particular arrangementsdisclosed are meant to be illustrative only and not limiting as to thescope, which is to be given the full breadth of the appended claims andany equivalent thereof.

EXAMPLES

The foregoing discussion may be better understood in connection with thefollowing representative examples which are presented for purposes ofillustrating the principle methods and compositions of the invention andnot by way of limitation. Various other examples will be apparent to theperson skilled in the art after reading the present disclosure withoutdeparting from the spirit and scope of the disclosure. It is intendedthat all such other examples be included within the scope of theappended claims.

All parts are by weight (e.g., % w/w), and temperatures are in degreescentigrade (° C.), unless otherwise indicated.

Cell Culture Methods

The MDA-MB-231 (MB-231) and MCF-7 cell lines were obtained from AmericanType Culture Collection (Manassas, Va.). The cell lines were maintainedat 37° C. in a humidified atmosphere of 95% air and 5% CO₂. MB-231 cellswere grown in RPMI (GIBCO®, Invitrogen™, Carlsbad, Calif.) containing10% fetal calf serum (Hyclone, Thermo Fisher Scientific, Waltham,Mass.), 0.5 mM L-glutamine (GIBCO®), 25 mg/ml glucose (Sigma-Aldrich),HEPES (GIBCO®) and Sodium Pyruvate (GIBCO®). MCF-7 cells were grown inDMEM (GIBCO®) supplemented with 10% fetal calf serum.

HuR Immunoprecipitations (RIP-Chip)

HuR RIP-Chip analysis was performed as previously described [Intine R Vet al., Mol Cell 2003, 12(5):1301-130; Atasoy U et al., J Immunol 2003,171(8):4369-4378; Casolaro V et al., The Journal of Allergy and ClinicalImmunology 2008, 121(4):853-859 e854]. Briefly, lysates were preparedfrom exponentially growing MB-231 and MCF-7 cells. Equal amounts ofprotein lysates were used (100-300 μg). HuR monoclonal antibody 3A2(made in our laboratory from the 3A2 hybridoma, generously provided byDr. Joan Steitz, Yale University, New Haven, Conn.) or isotype controlIgG1 (BD Biosciences, San Jose, Calif.) were pre-coated onto protein ASepharose beads (PAS) and extensively washed. Lysates from each cellinitially were pre-absorbed with 30 μg of IgG1, and then removed byaddition of PAS beads. Individual pull down assays were performed at 4°C. for only 1-2 hr to minimize potential re-assortment of mRNAs.

RNA Amplification

The entire amount of recovered RNA per immunoprecipitation was amplifiedusing the WT-Ovation™ Pico RNA Amplification System protocol (NuGen, SanCarlos, Calif.). Forty ng of total RNA was used as starting material togenerate at least 6 μg of cDNA. Amplified cDNA was purified using ZymoResearch Clean and Concentrator™-25 (Zymo Research, Orange, Calif.).Three μg of amplified and purified cDNA was incubated at 50° C. for 30minutes with 5 μl of UNG buffer and 5 μl UNG enzyme and 60 minutes with5 μl labeling buffer and 5 μl ARP (biotin) solution as described inNuGen's labeling protocol for the Illumina Beadarray platform. Allsamples (total RNA, amplified cDNA, and biotin labeled amplified cDNA)were quantitated using a Nanodrop™ (Thermo Fisher Scientific, Waltham,Mass.) spectrophotometer. RNA quality and integrity were assessed onselected samples with the Experion™ automated electrophoresis system(Bio-Rad, Hercules, Calif.).

Microarray

Biotin-labeled, amplified cDNA (1.5 μg) was hybridized to a Sentrix®Human-6 v.2 Whole Genome Expression BeadChips (Sentrix Human WG-6;Illumina, San Diego, Calif.). Each chip tested 6 samples and contained47,293 gene targets, representing 18,025 distinct RefSeq genes that arenot pseudogenes. A total of 3 chips were used for this experiment. Thechips were hybridized at 48° C. for 20 hr in the hybridization bufferprovided by the manufacturer. After hybridization, the chips were washedand stained with streptavidin-C3. The chips were scanned on theBeadArray Reader, as described by Illumina. The Illumina Beadstudiosoftware was used to assess fluorescent hybridization signals.

Quantitative RT-PCR

Selected genes were validated by quantitative RT-PCR. Briefly, cDNA wasgenerated from the same samples as previously described for themicroarray experiments using 10 ng total RNA and the SuperScript™ IIIPlatinum® Two-Step qRT-PCR Kit with SYBR® Green (Invitrogen Carlsbad,Calif.). RT-PCR was performed on the StepOne™ Real-Time PCR System(Applied Biosystems, Foster City, Calif.). Each sample was run intriplicate for these genes and the cDNA was divided equally per reactionin a 20 μl volume. The PCR conditions were: 50° C. for 2 minutes and 95°C. for 2 minutes, followed by 40 cycles of 95° C. for 15 secondsalternating with 60° C. for 30 seconds. Melting curve analysis wasperformed on every reaction to confirm a single amplicon. For each cellline, differences in gene expression were determined using the equation2^(−ΔΔCt), where the C_(t) value for either the HuR or IgG IP wassubtracted from the C_(t) value of the GAPDH control. For each cellline, the ΔC_(t) value for the HuR and IgG IP were computed intriplicate and averaged to give one ΔΔC_(t) value per sample. Primersused:

Human RT GAPDH (SEQ ID NO: 1) Forward 5′ AGCCTCAAGATCATCAGCAATGCC 3′(SEQ ID NO: 2) Reverse 5′ TGTGGTCATGAGTCCTTCCACGAT 3′ Mouse RT HuR(SEQ ID NO: 3) Forward 5′ ACTGCAGGGATGACATTGGGAGAA 3′ (SEQ ID NO: 4)Reverse 5′ AAGCTTTGCAGATTCAACCTCGCC 3′ Human RT HuR (SEQ ID NO: 5)Forward 5′ ATGAAGACCACATGGCCGAAGACT 3′ (SEQ ID NO: 6) Reverse 5′AGTTCACAAAGCCATAGCCCAAGC 3′ Human RT CD9 (SEQ ID NO: 7) Forward 5′TCAGACCAAGAGCATCTTCGAGCA 3′ (SEQ ID NO: 8) Reverse 5′ACCAAGAGGAAGCCGAAGAACAGT 3′ Human RT CALM2 (SEQ ID NO: 9) Forward 5′CTGACCAACTGACTGAAGAGCAGA 3′ (SEQ ID NO: 10) Reverse 5′TTCTGTGGGATTCTGCCCAAGAG 3′

Cloning Strategy of HA HuR

A hemagglutinin (HA)-tagged human HuR gene [Gubin M M et al., Cell Cycle2010, 9(16):3337-46] was cloned into the NheI and XhoI sites of thepZeoSV2(−) vector (Invitrogen). The plasmids were sequenced in bothdirections to confirm identity. Cells were transfected with either pZeoHA HuR or pZeo empty vector using Lipofectamine 2000 (Invitrogen). Afterfive days, the transfected media was removed, and replaced with freshmedium containing 200 μg/ml of Zeocin antibiotic (Invitrogen). Cellswere selected for a ten day period. After ten days, the selected cellswere maintained in 50 μg/ml of Zeocin to maintain pZeo HA HuR and theempty expression vector control. No viable cells remained in theuntransfected well. Cells were then cloned by limiting dilution.

Lentiviral RNAi HuR Knockdown

To establish lentivirus to knockdown HuR, PSICOOLIGOMAKER v1.5 software(web.mit.edu/ccr/labs/jacks) was used to identify optimal shRNAssequences to HuR. We tested multiple sequences, and chose the followingsequence, designated shRNA H760, for further study:

shRNA H760 (SEQ ID NO: 11) 5′-GGATCCTCTGGCAGATGT-3′Sense and anti-sense DNAs (prepared by Integrated DNA Technologies, Inc,IDT, Coralville, Iowa) were annealed to form a duplex DNAs with stemloops and a hairpin, that were cloned into in the Lentilox pII3.7 vector(ATCC) between the HpaI and XhoI restriction sites.

The DNA inserts were verified by sequencing, and the resultinglentiviral DNAs were packaged in 293FT cells using a ViraPowerLentiviral Expression Systems kit (Invitrogen) according to the protocolprovided by the manufacturer. MB-231 and MCF-7 cells were both seeded ata density of 100,000 cells in 100 mm tissue culture plates with 10 ml ofmedia. The following day, lentiviruses expressing either GFP and noshRNA (empty lentilox control) or GFP and HuR shRNA H760, were added ata multiplicity of infection (MOI) of 10, along with polybrene (8 μg/ml)(Sigma-Aldrich Corp, St. Louis, Mo.). After five days, cells wereharvested by trypsinization and sorted for GFP expression using BDFACSDiva cell sorter (BD Bioscience). Cells were cloned by limitingdilution and GFP expression was assessed using FACScan (BD Bioscience)and Cell Quest software (BD Bioscience). GFP expression was >98%,indicating a homogenous cell population.

SDS-PAGE and Western Blot Analysis

Western analysis was performed as described previously, with slightmodifications [Atasoy U et al., J Immunol 2003, 171(8):4369-4378].Briefly, cells were harvested and lysed in triple-detergent RIPA buffer,with a protease inhibitor cocktail (Roche, Pleasanton, Calif.). Fornuclear and cytoplasmic fractionations, the NE-PER kit was used (Pierce,Rockford, Ill.). Protein quantity was determined by Bradford Assay.Forty μg samples of protein were separated by electrophoresis on a 12%SDS-polyacrylamide gel and transferred to a nitrocellulose membrane. Themembrane was blocked with 5% nonfat milk powder at room temperature for1 hr and incubated with anti-β-tubulin (1 μg/ml, Sigma-Aldrich) at 4° C.overnight. After washing, the membrane was incubated with monoclonalanti-HuR clone 3A2 antibody (1 μg/ml) at room temperature for 1 hr oranti-CD9 antibody (1:100) (Santa Cruz Biotechnology, Inc., Santa Cruz,Calif.) at 4° C. overnight. The secondary antibody, a sheep anti-mouseIg horse radish peroxidase (1:4000) (GE Healthcare, Piscataway, N.J.),was used with an incubation period of 1 hour at room temperature.Specific proteins were detected using chemiluminescence (GE Healthcare).HuR knockdown was determined to be >90% using Bio-Rad's Quantity Onesoftware (Bio-Rad) normalizing to β-tubulin, and HuR overexpression wasquantitated in a similar manner.

Biotin Pull-Downs

Biotinylated transcripts were synthesized using cDNA that was preparedfrom MB-231 cells. Templates were prepared using forward primers thatcontained the following T7 RNA polymerase promoter sequence:

[T7] (SEQ ID NO: 12) CCAAGCTTCTAATACGACTCACTTATAGGGAGA

Primers used for the preparation of biotinylated transcripts spanningthe CD9 CR, and 3′UTR (NM_(—)001769) and CALM2 CR and 3′UTR(NM_(—)001743.3) were as follows:

CD9 CR 118-560: [T7] (SEQ ID NO: 13) 5′ TCAAAGGAGGCACCAAGTGCAT 3′ and(SEQ ID NO: 14) 5′ AACGCATAGTGGATGGCTTTCA 3′ CD9 3′UTR 798-1231: [T7](SEQ ID NO: 15) 5′ AGTCAGCTTACATCCCTGAGCA 3′ and (SEQ ID NO: 16) 5′GACATTGTCATAATTTTTTATTATGTATC 3′ CALM2 CR 72-515: [T7] (SEQ ID NO: 17)5′ GCTGACCAACTGACTGAAGA 3′ and (SEQ ID NO: 18) 5′CTTTGCTGTCATCATTTGTACAAA 3′ CALM2 3′UTR 518-1128: [T7] (SEQ ID NO: 19)5′ AGACCTTGTACAGAATGTGTTAA 3′ and (SEQ ID NO: 20) 5′GGGTAAATTGTAATTTTTTTATTGGAA 3′ GAPDH 3′UTR: [T7] (SEQ ID NO: 21) 5′CCTCAACGACCACTTTGTCA 3′ and (SEQ ID NO: 22) 5′GGTTGAGCACAGGG TACTTTATT 3′

The PCR-amplified fragments were purified and used as templates for invitro synthesis of the corresponding biotinylated RNAs using aMAXIscript kit (Ambion®, Applied Biosystems). Biotin pull-down assayswere performed by incubating 40 μg of MB-231 cell lysates with equimolaramounts of biotinylated transcripts for 1 hr at room temperature. Thecomplexes were isolated using paramagnetic streptavidin-conjugatedDynabeads (Dynal®, Invitrogen), and the bound proteins in the pull-downmaterial were analyzed by Western blotting using an antibody recognizingHuR (Santa Cruz). After secondary-antibody incubations, the signals werevisualized by chemiluminescence (Amersham Biosciences, GE Healthcare).

Statistical Analysis of Microarray Data

Analysis of microarray gene expression data was primarily performedusing the Linear Models for Microarray Data (limma) package [Smyth G,In. Edited by Gentleman R C V, Dudoit S, Irizarry R, Huber W. New York:Springer; 2005] and the lumi package [Du P et al., Bioinformatics 2008,24(13):1547-1548], available through the Bioconductor project [GentlemanR C et al., Genome Biol 2004, 5(10):R80] for use with R statisticalsoftware [Team R D C, In: ISBN 3-900051-07-0. vol.http://www.r-project.org: R Foundation for Statistical Computing Vienna,Austria; 2006]. After data pre-processing was completed the statisticalanalysis was performed using moderated t-statistics applied to thelog-transformed (base 2) normalized intensity for each gene using anEmpirical Bayes approach [Smyth G K, Stat Appl Genet Mol Biol 2004,3:Article 3]. Three contrasts of interest were computed and tested. Thefirst was the difference between HuR pulldown and IgG background for theMB-231 cell line. Genes which exhibited significantly greater expressionin the pull-down assays were considered to be in the HuR pellet for theMB-231 cell line. The second contrast was similar to the first, but forthe MCF-7 cell line. The third and most important contrast, was thedifference between the first and second contrast, and can be viewed as atest of statistical interaction between HuR and the cell line. For agiven gene, this term can be interpreted as reflection of thesynergistic relationship between HuR and estrogen in breast cancer.Adjustment for multiple testing was made using the false discovery rate(FDR) method of Benjamini and Hochberg [Journal of the Royal StatisticalSociety 1995, Series B 57:289-300] with an FDR of 10% as our cutoff fordeclaring significance. To facilitate interpretation, log-fold-changeswere transformed back to fold-changes on the data.

Gene ontology (GO) analyses were carried out on the list of significantgenes based on the third contrast described above. The purpose of theanalyses was to test the association between Gene Ontology Consortiumcategories [Consortium T G O, Nat Genetics 2000, 25:25-29] anddifferentially-expressed HuR pellet genes between MB-231 and MCF-7.Using our defined gene universe, GOstats [Falcon S, Gentleman R,Bioinformatics 2007, 23(2):257-258] was used to carry out conditionalhypergeometric tests. These tests exploit the hierarchical nature of therelationships among the GO terms for conditioning [Alexa A et al.,Bioinformatics 2006, 22:1600-1607]. We carried out GO analyses forover-representation of biological process (BP), molecular function (MF),and cellular component (CC) ontologies, and computed the nominalhypergeometric probability for each GO category. These results were usedto assess whether the number of selected genes associated with a giventerm was larger than expected, and a p-value cutoff of 0.01 was used. GOcategories containing less than 10 genes from our gene universe were notconsidered to be reliable indicators, and are not reported.

Microarray Data Preprocessing

Data quality was examined by looking at quality controls metricsproduced by Illumina's software (BeadStudio v3.1.3.0, Gene ExpressionModule 3.2.7). The data were then exported for further analyses. R.Image plots of each array were examined for spatial artifacts, and therewas no evidence of systematic effects indicative of technical problemswith the arrays. Within limma, quantile normalization was used forbetween chip normalization. Finally, quality control statistics werecomputed using a variety of Illumina's internal control probes that arereplicated on each array. Any probes which were considered “notdetectable” across all samples were excluded from further statisticalanalyses in order to reduce false positives. The determination of “notdetectable” was based upon the BeadStudio computed detection p-valuebeing greater than 1%.

Gene Ontology Gene Universe

In defining the gene universe for the analysis, non-specific filteringwas used to increase the statistical power without biasing the results.We started with all probes on the Illumina array which had both anEntrez gene identifier [Maglott D et al., Nucleic Acids Res 2005,33(Database issue):D54-58] and a GO annotation, as provided in thelumiHumanAll.db [Du P et al., R package version 1.12.0] annotation datapackage and GO.db [Carlson M et al., R package version 2.4.5] annotationmaps (built using data obtained from NCBI on Apr. 2, 2008). This set wasthen reduced by excluding probes that exhibited little variability(interquartile range (IQR) of <0.1 on log₂ scale) across all samplesbecause such probes are generally not informative. Finally, for probesthat mapped to the same Entrez identifier, a single probe was chosen inorder to insure a subjective map from probe IDs to GO categories (viaEntrez identifiers). This was necessary to avoid redundantly counting GOcategories which produces false positives. Probes with the largest IQRwere chosen to be associated with an Entrez identifier.

Example 1 Identification of Genes in Estrogen Receptor-Positive (ER+)and Estrogen Receptor-Negative (ER−) Breast Cancer Cell Lines Using RIPChips

Distinct subsets of RNP-associated mRNAs in two breast cancer celllines, MDA MB231 estrogen receptor negative (ER−) and MCF-7 estrogenreceptor positive (ER+) were identified using a modified protocol usingRIP chips, as described below. Briefly, method includes the steps of (1)preparing polysomal lysates; (2) performing immunoprecipitation with RBPantibodies; (3) extracting RNA; (4) amplifying and labeling recoveredRNA, and (5) hybridizing to genome-wide microarrays.

The technology can also be used to facilitate the identification andcharacterization of well known and novel genes targeted byribonucleotide binding proteins, including genes involved in theregulation of cancer and related metabolic pathways.

HuR Immunoprecipitations from ER+ and ER− Breast Cancer Cell Lines

We first determined HuR protein expression levels in breast cancer celllines. HuR is expressed in both the ER− and the ER+ cell lines, MB-231and MCF-7, respectively (FIG. 1A). RNA immunoprecipitations, using HuRmonoclonal antibody 3A2, recovered HuR (FIG. 1A) and revealed, byquantitative RT-PCR, a significant enrichment of up to fifteen fold fora known HuR target, B-ACTIN mRNA, as compared to isotype control (IgG1)and normalized to a non-target, GAPDH mRNA (FIG. 1B). These data showedthat HuR RIP specifically immunoprecipitate HuR protein and associatedmRNAs, though absolute quantitative conclusions cannot be drawn sincedifferent amounts of lysates were used and efficiency ofimmunoprecipitation from different cell lines may differ.

RIP-Chip from ER+ and ER− Breast Cancer Cell Lines Identifies UniqueSets of Associated mRNAs

RIP-Chip was performed on cytoplasmic lysates from both breast cancercell lines with HuR antibody and isotype control in order to determineHuR associated mRNAs. Each immunoprecipitation was done at least threeindependent times with matching controls. Signals from isotype controlwere subtracted out. Recovered mRNA was amplified and hybridized toIllumina Sentrix Human arrays consisting of 47,000 genes. FIG. 2represents a composite array generated by combining hybridizations totwelve different arrays (log 2 scale). Three groups of HuR-associatedtarget genes were identified: MB-231 targets in the left upper quadrant;both MB-231 and MCF-7 targets in the right upper quadrant; MCF-7 targetsin the right lower quadrant. As expected, most of the mRNAs did notassociate with HuR and were located in the lower left quadrant. Therewere 395 and 64 annotated genes, at least 2-fold or more enriched,associated with either MB-231 or MCF-7 cells, respectively, and 182genes associated with both cell lines. A complete list can be found inTable 1.

TABLE 1 Complete GO analysis: Listing of HuR-associated genes with oddsratios and functional categories. P Odds Exp GOID value Ratio CountCount Size Term Genes Molecular Function GO: 0005515 0 1.88 64.14 833798 protein binding NAMPT^(2.17), SPRY1^(2.53), SSSCA1^(0.46),RAD51AP1^(2.01), FRS3^(2.69), TMED2^(2.8), KDELR2^(2.21), FOXN3^(2.62),FBXO27^(2.03), DCBLD2^(2.54), LAYN^(2.25), E2F7^(2.24), CSNK1E^(4.06),CSNK2B^(2.7), CSTF3^(2.09), CNKSR3^(2.48), KIAA1949^(2.2),DPYSL2^(2.76), KCTD6^(2.57), EREG^(2.86), ERH^(2.07), PHLDA1^(2.57),SYNE1^(2.02), KIAA0999^(2.01), COTL1^(3.84), GATA3^(0.28), GJA1^(2.06),LSM1^(2.1), KIAA1267^(2.16), CNOT7^(2.29), HSPA1A^(0.34), IFNGR2^(2.94),IL8^(2.87), ITGAE^(2.34), ACAT1^(2.4), RHOB^(0.39), MARCKS^(3.21),MAX^(2.35), RAB8A^(2.38), TRIM37^(0.4), MYB^(0.2), NFYC^(2.16),NPY1R^(0.33), GAL^(2.18), PCNA^(2.51), LEF1^(3.79), SPG21^(2.51),UFM1^(2.43), RASD1^(2.07), POLR2H^(2.05), RIN2^(2.06), ALS2CR2^(2.1),CAMK2N1^(2.01), NOLA3^(3.18), PRKAR1A^(0.28), PCID2^(2.44), TWSG1^(2.3),RDX^(2.14), BDNF^(2.36), RNF25^(0.48), NSD1^(2.21), PHACTR4^(2.16),SSR3^(2.54), STAU1^(2.53), TAF13^(2.15), C1QBP^(2.72), TNFRSF1A^(2.36),TXN^(3.01), UBE2I^(2.29), MALL^(2.51), CALR^(2.18), CAMLG^(0.39),NCOA3^(0.19), CSDA^(2.43), COPS3^(2.45), CAV1^(2.05), KHSRP^(2.49),RUNX1^(2.17), AP1S2^(2.93), MED20^(2.28), ATP6V1G1^(0.32), RBX1^(2.65),CDC42^(2.76) GO: 0016563 0 3.59 3.07 10 182 transcription activatorETV5^(2.03), GATA3^(0.28), CNOT7^(2.29), MAX^(2.35), MYB^(0.2), activityNFYC^(2.16), LEF1^(3.79), COA3^(0.19), RUNX1^(2.17), CHURC1^(0.38) GO:0003924 0 4.34 1.77 7 105 GTPase activity ARL4A^(2.13), TUBB3^(2.44),ARF4^(2.25), RHOB^(0.39), RND3^(2.29), RASD1^(2.07), CDC42^(2.76)Biological Component GO: 0009893 0 3.21 4.53 13 271 positive regulationof EREG^(2.86), ETV5^(2.03), GATA3^(0.28), GJA1^(2.06), CNOT7^(2.29),metabolic process FOXA1^(0.2), LEF1^(3.79), NSD1^(2.21),TNFRSF1A^(2.36), UBE2D1^(2.19), NCOA3^(0.19), RUNX1^(2.17),CHURC1^(0.38) GO: 0045935 0 3.49 3.51 11 210 positive regulation ofEREG^(2.86), ETV5^(2.03), GATA3^(0.28), CNOT7^(2.29), FOXA1^(0.2),nucleobase, nucleoside, LEF1^(3.79), NSD1^(2.21), TNFRSF1A^(2.36),NCOA3^(0.19), RUNX1^(2.17), nucleotide and nucleic CHURC1^(0.38) acidmetabolic process GO: 0010557 0 3.3 3.7 11 221 positive regulation ofEREG^(2.86), ETV5^(2.03), GATA3^(0.28), CNOT7^(2.29), FOXA1^(0.2),macromolecule LEF1^(3.79), NSD1^(2.21), TNFRSF1A^(2.36), NCOA3^(0.19),biosynthetic process RUNX1^(2.17), CHURC1^(0.38) GO: 0007165 0 1.8328.57 43 1708 signal transduction ARL4A^(2.13), NAMPT^(2.17),SPRY1^(2.53), TUBB3^(2.44), FRS3^(2.69), FOXN3^(2.62), DCBLD2^(2.54),CSNK1E^(4.06), CSNK2B^(2.7), CNKSR3^(2.48), DPYSL2^(2.76), EREG^(2.86),GJA1^(2.06), CNOT7^(2.29), HMGB2^(2.32), IFNGR2^(2.94), IL8^(2.87),ITGAE^(2.34), ARF4^(2.25), RHOB^(0.39), RND3^(2.29), RAB8A^(2.38),NPY1R^(0.33), GOLT1B², GAL^(2.18), PCNA^(2.51), LEF1^(3.79),SPG21^(2.51), RASD1^(2.07), RIN2^(2.06), PRKAR1A^(0.28), CXCR7^(0.1),TWSG1^(2.3), RPS6KB1^(0.24), TNFRSF1A^(2.36), TXN^(3.01), UBE2D1^(2.19),CAMLG^(0.39), NCOA3^(0.19), COPS3^(2.45), CAV1^(2.05), MTA1^(2.68),CDC42^(2.76) GO: 0048514 0 5.11 1.3 6 78 blood vessel EREG^(2.86),GJA1^(2.06), IL8^(2.87), RHOB^(0.39), CAV1^(2.05), RUNX1^(2.17)morphogenesis GO: 0010628 0 3.24 3.4 10 203 positive regulation ofETV5^(2.03), GATA3^(0.28), CNOT7^(2.29), FOXA1^(0.2), LEF1^(3.79), geneexpression NSD1^(2.21), TNFRSF1A^(2.36), NCOA3^(0.19), RUNX1^(2.17),CHURC1^(0.38) GO: 0030855 0 12.91 0.28 3 17 epithelial cell GJA1^(2.06),FOXA1^(0.2), CAV1^(2.05) differentiation GO: 0048646 0 4.66 1.42 6 85anatomical structure EREG^(2.86), IL8^(2.87), RHOB^(0.39), LEF1^(3.79),TWSG1^(2.3), RUNX1^(2.17) formation GO: 0048522 0 2.18 9.72 19 581positive regulation of NAMPT^(2.17), EREG^(2.86), ETV5^(2.03),GATA3^(0.28), GJA1^(2.06), cellular process CNOT7^(2.29), FOXA1^(0.2),GOLT1B², GAL^(2.18), LEF1^(3.79), TWSG1^(2.3), NSD1^(2.21),TNFRSF1A^(2.36), UBE2D1^(2.19), NCOA3^(0.19), RUNX1^(2.17),PDCD5^(2.49), CHURC1^(0.38), CDC42^(2.76) GO: 0042445 0 7.13 0.64 4 38hormone metabolic GATA3^(0.28), FOXA1^(0.2), GAL^(2.18), SRD5A1^(2.23)process GO: 0001944 0 4.38 1.51 6 90 vasculature EREG^(2.86),GJA1^(2.06), IL8^(2.87), RHOB^(0.39), CAV1^(2.05), RUNX1^(2.17)development GO: 0048518 0 6.69 0.67 4 44 positive regulation ofIL8^(2.87), RHOB^(0.39), SPG21^(2.51), CAV1^(2.05) biological processGO: 0045893 0.01 3.21 2.71 8 162 positive regulation of GATA3^(0.28),CNOT7^(2.29), FOXA1^(0.2), LEF1^(3.79), transcription, DNA- NSD1^(2.21),TNFRSF1A^(2.36), NCOA3^(0.19), RUNX1^(2.17) dependent GO: 0006357 0.012.54 4.7 11 281 regulation of CNOT7^(2.29), HMGB2^(2.32), FOXA1^(0.2),NFYC^(2.16), LEF1^(3.79), transcription from RNA PRKAR1A^(0.28),NSD1^(2.21), TNFRSF1A^(2.36), CSDA^(2.43), RUNX1^(2.17), polymerase IIpromoter MED20^(2.28) Cellular Component GO: 0005794 0 2.5 7.05 16 413Golgi apparatus TMED2^(2.8), KDELR2^(2.21), SYNE1^(2.02), CHIC2^(3.76),GJA1^(2.06), ARF4^(2.25), RND3^(2.29), GOLT1B², GAL^(2.18),C4orf18^(0.47), SPG21^(2.51), CHPT1^(3.06), MALL^(2.51), CAV1^(2.05),ST3GAL5^(2.18), AP1S2^(2.93) GO: 0000139 0 2.84 3.81 10 223 Golgimembrane TMED2^(2.8), GJA1^(2.06), RND3^(2.29), GOLT1B², C4orf18^(0.47),CHPT1^(3.06), MALL^(2.51), CAV1^(2.05), ST3GAL5^(2.18), AP1S2^(2.93) GO:0005798 0.01 6.22 0.72 4 42 Golgi-associated vesicle CHIC2^(3.76),GJA1^(2.06), SPG21^(2.51), AP1S2^(2.93) GO: 0000793 0.01 5.62 0.79 4 46condensed CENPA^(2.06), C18orf24^(3.04), HMGB2^(2.32), UBE2I^(2.29)chromosome NOTE: Subscripts denote fold change of(MDA_3A2/MDA_IgG)/(MCF_3A2/MCF_IgG)

Tables A3 and A4, at the end of this document, list genes which areoverexpressed in MCF-7 cells, and those which are overexpressed in MDAMB231 cells, respectively. The complete set of genes is also availablein the NCBI database (Accession number GSE17820) at the following link:http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=pdsnrqmiawukqlm&acc=GSE17820.

These genes generally fell into three groups. Group 1 consisted ofcancer-associated genes which were known HuR targets, such as PTMA mRNA.Group 2 consisted of genes which played a role in cancer but were notknown to be HuR targets. Group 3 consisted of genes with an unknownfunction in cancer, but which may be regulated by HuR. These datarevealed that HuR was associated with distinct subsets of mRNAs in ER+and ER− breast cancer cells.

Gene Ontology (GO) analyses of differentially expressed significantgenes between ER+ and ER− cells were categorized into Biological Process(BP), Cellular Component (CC), and Molecular Function (MF). GO analysesallows for the identification of gene families that may play significantroles related to these categories in expression profiles. Most of thedifferentially-expressed genes (155) were found to be more abundant thanexpected in 14 BP categories (FIG. 3A). Three MF categories consisted of100 genes with most of these (83) related to protein binding andtranscription activator activity. The CC categories contained the least(34) and were primarily associated with the Golgi apparatus. For thecomplete GO analyses, see Table 1. In Table 1, we list the topHuR-associated mRNAs in the different categories which wereapproximately 5 fold enriched or greater. As can be seen in FIG. 3B, apartial listing of some of these genes (in bold) are candidate membersto be involved in multiple areas of cancer control, as suggested byHanahan and Weinberg (Cell 2000, 100(1):57-70). We note that thoughB-ACTIN mRNA was amongst the most abundant of HuR-associated mRNAs inMCF-7 cells, B-ACTIN mRNA levels were only 3.93-fold higher in HuR IPcompared to IgG IP, and hence less than the 5-fold cut-off we employedfor Table 2. Taken together, novel HuR-controlled genes have beenidentified, which may play roles in breast carcinogenesis in a cancersubtype-specific fashion.

TABLE 2 HuR Targets Approximately Five-Fold or Greater In DecreasingOrder* Listing of HuR-associated mRNAs in MB-231 and MCF-7 cell lines.Both Cell MB-231 Cells MCF-7 Cells Lines CD9 ACTB SMNDC1 MAL2 CALM2 PTMACALM2 CDK2AP1 hCG_1781062 SRRM1 UBE2E2 JUND ARL6IP1 PTMA CCNI CCNIATP6V1G1 ACTB HMGB1 DAZAP2 CKLF BUB3 PJA2 LOC203547 CD9 SRRM1 NPM1 MATR3TMC01 ARL6IP1 STK4 CXCR7 ZFP36L1 SFRS2 PTMA FKBP1A TMSL3 PLOD2 PPP6CATP1B1 PMP22 EIF4A2 RPS6KB1 HSPA1A MMD CALM2 TIMEM59 FOXA1 PEX11B TMCO1MMD MYB CD9 ZNF14 CSDA ITGB1 PARD6B LOC441087 CHIC2 SRRM1 SNX16 PUM1DAZAP2 MORF4L1 TFDP1 MMD ZNF22 GCA CISD2 C4orf34 ATP1B1 DAZAP2 G3BP1C21orf55 TRAM1 NCOA3 ATP1B1 SFPQ ENY2 PRKAR1A YBX1 HIST1H3E ALKBH5 CCNICSTB C15orf51 RAP2A YWHAZ PRIM2 SLC7A1 TMCO1 C15orf15 PCBP2 ROD1 ARL6IP1SPINT2 CALMG YTHDC1 *The complete set of gene are up-loaded to NCBIdatabase at the following link:http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=pdsnrqmiawukqlm&acc=GSE17820.(NCBI Accession number GSE17820).

Validation of HuR Targets CD9 and CALM2 by Real-Time PCR and BiotinPull-Down Analyses

In order to validate HuR binding to genes identified in FIG. 2, we chosetwo known cancer associated genes, CD9 and CALM2, which were highlyexpressed in both cell lines. Two independent approaches confirmed thephysical interaction between HuR, CD9 and CALM2 mRNAs. Precipitated mRNAfrom the RIP-Chip experiments were analyzed by RT-PCR. Both CD9 andCALM2 mRNAs were enriched in the HuR RIP by as much as 160-fold (FIGS.4A and 4B), but not the isotype control IP. We further confirmed HuRbinding to CD9 and CALM2 mRNAs by biotin pull-down assays. The relevantportion of the mRNA was transcribed with biotin tags, and incubated withlysates from the two cell lines to probe for interactions with protein.The mixtures were then separated by pull-down assays usingstreptavidin-coated beads, and HuR levels were analyzed by Western blotanalysis. As shown in FIG. 5, HuR specifically interacts with CD9 andCALM2 mRNAs in the 3′UTR regions, but not within the coding region (CR)or with a control biotinylated RNA corresponding to the 3′UTR of thehousekeeping control GAPDH mRNA, which is not a target of HuR.

HuR Differentially Regulates CD9 and CALM2 in MB231 and MCF-7 Cell Lines

To gain insight into the biological effects of these associations, westudied the consequences of stably increasing or decreasing HuRabundance. Individual MB-231 clones which over- and under-express HuRwere established by limiting dilution (FIGS. 6A and 6B). MB-231 cellsoverexpressed HuR by 140% (FIG. 6A). HuR knock down assays usinglentiviral shRNA reported a ˜95% reduction in HuR expression (FIG. 6B).Surprisingly, overexpression of HuR in MB-231 cells caused decreases inboth CD9 mRNA and protein levels (FIGS. 6C and 6D). HuR knock downassays, however, reported increases in both CD9 mRNA and protein levels(FIGS. 6C and 6E). This is the opposite of what we predicted, since HuRis generally regarded as a stabilizer of mRNA. In contrast,overexpression of HuR in MB-231 cells did not significantly alter thelevels of CALM2 mRNA (FIG. 6D). FIG. 6F shows a graphical analysis,which reveals that HuR over-expression decreases both CD9 mRNA andprotein levels, compared to controls (dashed line set at 100%). The HuRshRNA knock-down experiments demonstrate increases in both CD9 mRNA andprotein levels above control levels.

Similar analyses were performed with MCF-7 cells, which demonstratedthat the over-expression levels of HA HuR were less than expected,approximately 10%, since this was a pooled population and we were unableto obtain MCF-7 clones which over-express HuR. In contrast, we generatedMCF-7 clones with reduced HuR levels (93%) using lentiviral shRNA (FIG.7B). Western blot analysis of MCF-7 cells which over-express HuRrevealed modest increases in CD9 protein levels (FIG. 7C). There arealso modest decreases in CD9 protein expression in MCF-7 with reducedHuR levels (FIG. 7C). mRNA levels of CD9 and CALM2 are essentiallyunchanged in MCF-7 cells which over-express HuR (FIG. 7D). As expected,HuR knock-down in MCF-7 cells using the lentiviral shRNA resulted insignificant reductions in both CD9 and CALM2 mRNA levels (FIG. 7E). Theright subpanel in FIG. 7E indicates the efficiency of HuR mRNAknock-down, which is consistent with the protein data (FIG. 7B). Theseresults are summarized in FIG. 7F. There are no significant changes seenin CD9 mRNA and CD9 protein for HuR over-expression. There is a morepronounced knock-down, however, in CD9 mRNA in MCF-7 cells which havereduced HuR levels.

The results of HuR shRNA knock down experiments in MCF-7 cells were asexpected, but opposite of those seen for MB-231 cells. Steady-state mRNAlevels of CD9 and CALM2 mRNAs decreased, consistent with the hypothesisthat HuR generally stabilizes its mRNA targets. One possible explanationof these disparate results is different levels of total cellular orcytoplasmic HuR. We performed nuclear and cytoplasmic fractionation(FIG. 8). These results demonstrate a modest (approximately 10%) greatercytoplasmic levels of HuR in MB-231 cells compared to MCF-7 cells. Thetotal cellular HuR levels are very similar for both MB-231 and MCF-7cells. Taken together, these results indicated that HuR appeared todifferentially regulate the same mRNAs, in a manner dependent upon thecellular milieu.

RIP-Chip technologies were used to define differentially regulated HuRgenes in ER+ and ER− breast cancer. Presented is a side-by-sidegenome-wide comparison of HuR-associated targets in wild-type ER+ andER− breast cancer cells. These findings demonstrate that HuR interactswith small subsets of genes involved in breast cancer, out of thepossible 8% of human genes possessing AREs which are potential targetsof HuR. Three broad categories of HuR targets were identified. First,there was a subset of targets only found in ER+ breast cancer. Second,there was a unique subset of HuR targets found only in ER− breastcancer. A third subset consisted of HuR-associated mRNAs common to bothforms of breast cancer, many of which were previously described ashaving roles in cancer.

We selected and validated two HuR targets, CD9 and CALM2 mRNAs, whichwere found in high abundance in both types of breast cancer. Initially,we employed the previously developed “heat map” signature of HuR bindingto gain insight into putative HuR target sequences [Lopez de Silanes Iet al., Proc Natl Acad Sci USA 2004, 101(9):2987-2992]. HuR binding wasverified by HuR immunoprecipitations, and analyzed by quantitativeRT-PCR and biotin pull-down assays. Both targets were enriched in HuRRIPS, compared to isotype control IP reactions. Biotin pull-down assaysverified the binding of HuR protein specifically to the 3′UTR regions ofboth mRNAs, as had been predicted.

CD9, for example, is a tetraspanin molecule which plays important rolesin cellular development, activation, growth and motility. It has beenimplicated in a variety of cancers, including gastric cancers and B cellacute leukemia [Lafleur M A et al., Mol Biol Cell 2009, 20(7):2030-2040;Nakamoto T et al, Gastroenterol 2009, 44(9):889-896; Nishida H et al.,Biochem Biophys Res Commun 2009, 382(1):57-62].

The role of CALM2 in cancer is less well understood, but may be linkedto cancer since it is involved in controlling calcium signaling[Coticchia C M et al., Breast Cancer Res Treat 2009, 115(3):545-560;Schmitt J M et al., Mol Cell Biochem 2009, 335(1-2):155-171.1 There arethree CALMODULIN genes (CALM1, CALM2 and CALM3) highly expressed in bothMB-231 and MCF-7 cell lines (FIG. 9). Although they are encoded bydifferent genes at different chromosomal locations, all three encode thesame open reading frame but differ in the 5′ and 3′ untranslated (UTRs)regions [Coticchia CM et al., Breast Cancer Res Treat 2009,115(3):545-560; Berchtold M W et al., Genomics 1993, 16(2):461-465;Fischer R et al., J Biol Chem 1988, 263(32):17055-17062]. Of the three,only CALM2 mRNA interacts with HuR by RIP analysis. Previously publishedreports have also indicated the necessity of knocking down all threeCALMODULIN mRNAs by siRNA to achieve knock down of the protein[Coticchia C M et al., Breast Cancer Res Treat 2009, 115(3):545-560].Therefore, differential HuR-associated regulation of the CALMODULINgenes appears to be involved in breast cancer, requiring additionalstudies at a molecular level.

The regulation of both CD9 and CALM2 target genes appeared to bedependent upon the cellular milieu. To test the functional consequencesof HuR binding to these two transcripts, we prepared cells that stablyexpressed higher or lower amounts of HuR, compared to the parent cells,in both ER+ and ER− breast cancer cell lines. HuR appeared todifferentially regulate the expression of CD9 in opposite directions inthe two different forms of breast cancer. Specifically, HuRoverexpression in ER− breast cancer (MB-231) unexpectedly decreased CD9mRNA and protein levels, while HuR knock down experiments demonstratedan increase in CD9 mRNA levels. This is usually the opposite of what ispredicted for most HuR targets, since HuR is thought to stabilize itsmRNA targets and often increases their translation. There did not seemto be similar effects upon CALM2 expression. As expected, knock down ofHuR by shRNA decreased expression of CD9 and CALM2 in ER+ breast cancer(MCF-7). Though there are differences in cytoplasmic HuR levels inMB-231 cells as compared with MCF-7, these are modest (10%). This is inkeeping, however, with observations that MB-231 cells are moreundifferentiated and more aggressive.

Analysis of HuR-associated mRNAs in both ER+ and ER− breast cancerrevealed three broad categories of genes. First, there were well knowncancer genes, such as PTMA, which are regulated by HuR [Lal A et al.,Embo J 2005, 24(10):1852-1862]. Second, there were cancer-related genes,such as CD9 and CALMODULIN, which were not known to be HuR regulated,until this report. Third, there were other genes identified by HuRassociation with unknown cancer functions, which could represent novelcancer targets. Demonstration of HuR involvement in the regulation ofother known cancer genes, such as CD44 and GATA-3, may offer insightsinto the regulation of these and similar cancer targets Tables A3 andA4. Taken together, these results may reveal insights intopost-transcriptional regulation of many genes which are known to beassociated with cancer, and facilitate the identification of previouslyunknown genes with similar or novel roles in regulating genes associatedwith cancer.

Without being bound by mechanisms of the HuR differential regulation ofCD9 and CALM2, it may be involved in microRNA (miRNA) regulation. In arecent report, we described the recruitment by HuR of miRNA let-7 totranslationally silence C-MYC expression [Kim H H et al., Genes & Dev2009, 23: 1743-1748]. It is clear from the findings of laboratoriesheaded by Filipowicz, Steitz and other investigators, that RBPs andmiRNAs are involved in intricate associations to affect downstreamtranslational suppression or activation of target mRNAs to help meetcellular needs [Bhattacharyya S N et al., Cell 2006, 125(6):1111-1124;Vasudevan S, Steitz J A, Cell 2007, 128(6):1105-1118]. Sharp andcolleagues proposed that different interactions between RBPs and miRNAsmay have evolved as a protective mechanism for the cell againstenvironmental stress [Leung A K, Sharp P A, Cell 2007, 130(4):581-585].

A remaining question is why HuR selectively binds to certain genescontaining AREs. Our previous work has demonstrated the role that HuRplays in myogenesis by stabilizing the expression of three criticalgenes involved in myogenesis: MYOD, MYOGENIN, and p21^(cip1) [Figueroa Aet al, Mol Cell Biol 2003, 23(14):4991-5004]. HuR overexpression resultsin precocious muscle differentiation and HuR siRNA knock down preventsmuscle differentiation [van der Giessen K et al., J Biol Chem 2003,278(47):47119-47128]. It is highly probable that there are more thanthree HuR targets inside these cells. A specific phenotype potentiallyarises when HuR levels are altered, which may involve interactions withmiRNAs.

Our findings share some similarity to earlier reports of HuR RIP-Chipanalysis of MCF-7 cells stably transfected with MCT-1 [Mazan-Mamczarz Ket al., Oncogene 2008, 27: 6151-6163]. These analyses, however, were notgenome-wide and employed transfected cells. Thrombospondin, a well-knownanti-angiogenic factor, was identified as a HuR-regulated target.Combined with earlier reports of the role of HuR in regulating, VEGF-αand HIF1α, HuR may be controlling a “posttranscriptional mini-operon”involved in angiogenesis [Levy A P, Trends Cardiovasc Med 1998,8(6):246-250; Sheflin L G et al., Biochem Biophys Res Commun 2004,322(2):644-651; Galban S et al., Mol Cell Biol 2008, 28(1):93-107].Xenograft animal models can also be used to investigate the role of HuRin breast cancer angiogenesis. The role of HuR in influencing expressionof various biomarkers can also be evaluated in breast tumors in vivo.

Post-transcriptional gene regulation is increasingly being appreciatedas a driver of malignant transformation. The roles of both RBPs andmiRNAs (so-called oncomirs) are being recognized in cancer[Esquela-Kerscher A, Slack F J, Nat Rev Cancer 2006, 6(4):259-269]. Manyreports have described alterations in miRNA expression profile andfunction as contributing to breast cancer malignant transformation andmetastasis [Iorio M V et al., Cancer Res 2005, 65(16):7065-7070; Ma L etal., Nature 2007, 449(7163):682-688; Ma L, Weinberg R A, Trends Genet2008, 24(9):448-456; Tavazoie S F et al., Nature 2008,451(7175):147-152]. HuR RIP-Chip analysis may shed further light intomalignant breast cancer transformation by identifying HuR associatedmRNAs.

The HuR-associated biomarkers may also be used in applications foridentifying drug resistance, specifically, tamoxifen resistance. Keeneand colleagues have described a potential mechanistic link between HuRexpression and tamoxifen drug resistance [Hostetter C et al., CancerBiol Ther 2008, 7(9)]. As breast cancer cells acquire tamoxifenresistance, there are increased levels of cytoplasmic HuR expression.Increased cytoplasmic HuR levels have previously been described insituations where HuR actively influences expression of cytoplasmictargets [Atasoy U et al., J Cell Sci 1998, 111 (Pt 21):3145-3156; AtasoyU et al., J Immunol 2003, 171(8):4369-4378; Casolaro V et al., TheJournal of Allergy and Clinical Immunology 2008, 121(4):853-859 e854].Drug resistance could be reversed by using siRNA to knock down HuRexpression, whereas exogenous overexpression of HuR could cause cells tobecome resistant to tamoxifen. HuR may be coordinately regulating geneswhich may allow a cell to acquire tamoxifen resistance. HuR-associatedtarget genes in ER+ cells is of particular interest.

Conclusion

In summary, using RIP-Chip analysis, we have performed a genome-widecomparison of HuR-associated targets in wild type ER+ and ER− breastcancer for the first time. We have identified novel HuR targets and havegained insight into HuR's potential role in regulating known cancergenes. We found distinct, differentially expressed subsets of HuR cancerrelated genes in ER+ and ER− breast cancer cell lines. Based on ourobservations, the enhanced expression of these mRNA subsets by HuR caninfluence many of the acquired capabilities of cancer cells. HuR's rolein regulating these genes may provide novel methods to facilitate thediagnosis of breast cancer and enhance the ability of physicians tomonitor the progress of therapies designed to treat breast cancer inpatients.

TABLE A3 Genes over expressed in MCF-7cells (Top Genes of Interest, Fold= MCF.3A2/MCF.IgG) PROB OF FOLD LOCUS LINK ID ID GENESYMBOL AVEEXPR T P.VALUE ADJ. P. VAL B DIFF EXP CHANGE 60 ZuropJSp8XsR4fiFL4 ACTB 10.045.11 0 0.01 0.32 0.58 12.94 805 Kvvgu6L7B3m6HOhLQQ CALM2 9.75 8.23 0 04.61 0.99 11.99 3727 3nGLUT17_w1_vZWv94 JUND 10.42 7.68 0 0 3.95 0.9811.31 9550 uF7uCSSUl8Cy1PfnDo ATP6V1G1 8.68 17.28 0 0 11.64 1 11.06 9184lSy3hs.Vfe1XLCVL54 BUB3 9.35 7.35 0 0 3.53 0.97 10.23 48693vtSvc_UIO77UA5e.I NPM1 9.64 7.11 0 0 3.22 0.96 10.15 57007E3u67.sWkajOgYAef4 CXCR7 8.1 47.13 0 0 17.97 1 9.96 7117upUK7Xkp7Dkvw0i5T8 TMSL3 10.1 8.46 0 0 4.87 0.99 9.77 1974KoV75wlUkJDXKyr8NU EIF4A2 9.17 7.05 0 0 3.14 0.96 9.71 9528BieNPnX3RdeU4x7S8U TMEM59 8.84 11.98 0 0 8.24 1 9.55 4602Ku.kHqiEgHuvjJS0eU MYB 8.41 26.22 0 0 14.93 1 9.47 3688WunOQSd0XGYt8f4vLk ITGB1 8.91 5.76 0 0.01 1.33 0.79 9.25 102503Qf0iXfs.oKegqVIf4 SRRM1 8.89 8.84 0 0 5.29 0.99 9.12 10933355S7.Q46EEioznsi4 MORF4L1 8.99 9.38 0 0 5.87 1 9 25801xvrrv4q_nIDgJej.uU GCA 8.48 24.81 0 0 14.54 1 8.73 98020Lt45pR09p1Ug9ch6s DAZAP2 9.11 8.19 0 0 4.56 0.99 8.69 82029UTgOHzqo64nuHn_eE NCOA3 8.34 19.45 0 0 12.65 1 8.38 5573cuQcHh3vPjV915X9Uo PRKAR1A 8.62 13.69 0 0 9.52 1 8.36 10983oioTn1X7UX_SXv3tOw CCNI 9.9 7.57 0 0 3.81 0.98 8.2 7534rpFefX_fk1RIc.V01w YWHAZ 9.06 6.11 0 0.01 1.84 0.86 8.19 51187frL7o56o4geDDf5ei4 C15orf15 8.9 10.38 0 0 6.85 1 7.99 10653xp59et6So6v5.oDXco SPINT2 8.63 8.29 0 0 4.68 0.99 7.81 102853Svt5P767C4E00S814 SMNDC1 8.71 13.04 0 0 9.05 1 7.81 Qi_4HrqWzsEnhQbgjE10 6.56 0 0 2.49 0.92 7.7 8099 rSCAiQVFAXBChVYEf0 CDK2AP1 9.55 5.74 00.01 1.3 0.79 7.6 23204 ZKnvriJIfiuOMvpd60 ARL6IP1 8.7 8.82 0 0 5.270.99 7.48 60 6EoLV_U1wCUVR93cKI ACTB 9.62 4.8 0 0.02 −0.17 0.46 7.4udBJ1LwOf4zLp1.kiU 8.23 16.17 0 0 11.05 1 7.17 9867 iJUrcDsOvr8_9zBVJUPJA2 8.44 7.3 0 0 3.46 0.97 7.14 9782 HpTDXI5GfcPTsXkTuE MATR3 8.73 7.390 0 3.58 0.97 7.13 677 l6PUrei.1DvDsBIHpE ZFP36L1 8.64 9.3 0 0 5.78 16.82 5352 uEC_Jfn31v_V.t2dc PLOD2 8.51 9.3 0 0 5.78 1 6.74 6198QPfSeXzyi5zirBF73k RPS6KB1 8.36 15.34 0 0 10.57 1 6.68 3169ZlNu5_.TUu85H9RL6E FOXA1 8.29 22.91 0 0 13.96 1 6.58 928rWSgWYjrci0nxNXiSg CD9 8.79 10.25 0 0 6.72 1 6.53 fgq.Uoebt514ne.ws48.54 6.36 0 0 2.2 0.9 6.38 84612 WN11QLno_Sk4mXJSgk PARD6B 8.81 4.95 00.02 0.06 0.51 6.15 64089 cy75e3vcCYFJR.9Dek SNX16 8.36 17.56 0 0 11.781 6.11 3_dx6HGuKOu4VTM4.0 9.69 4.96 0 0.02 0.08 0.52 6.11 7027TFXnpoyQh3ui.vS6xo TFDP1 9.31 4.47 0 0.03 −0.73 0.32 6.1 4938563GcqHr1KlETMUA3lTE CISD2 8.94 9.47 0 0 5.96 1 6.09 10146l693.PjqTkurvH6A6U G3BP1 8.89 5.69 0 0.01 1.22 0.77 6.050XXK56jxK7iUe70lDE 9.62 4.13 0 0.05 −1.31 0.21 6.04 481unu3iN6N5U0f6cuEqc ATP1B1 9 5.7 0 0.01 1.24 0.78 5.95 4904QrnhBSrkogQrIUuKSA YBX1 8.91 5.64 0 0.01 1.14 0.76 5.73 14763e78KW7T0IlK62aoQE CSTB 8.8 5.38 0 0.01 0.75 0.68 5.69 5558lbVIueo8a_4lHuXpf8 PRIM2 9.99 3.75 0 0.08 −1.97 0.12 5.69 5094c12iGrpOqJJyBDkj00 PCBP2 8.67 9.28 0 0 5.76 1 5.68 819ZrdJSVyIeffu.u097U CAMLG 8.5 10.8 0 0 7.24 1 5.58 114569fengk1X6LlOzC_pzyI MAL2 8.62 11.46 0 0 7.81 1 5.52 653226B4RV5U.3t.DwUK7yu8 hCG_1781062 8.56 6.73 0 0 2.72 0.94 5.43 5757QQ3z1iT1LB..uzsfJ4 PTMA 9.07 6.48 0 0 2.37 0.91 5.41 3146x5P787D9KKDHgTeLXo HMGB1 8.56 5.65 0 0.01 1.16 0.76 5.34 203547Ty5Xhyqij_jueT9CW4 LOC203547 8.99 5.55 0 0.01 1 0.73 5.2 54499uYd0KR7s5XkL6e3OJM TMCO1 8.53 9.17 0 0 5.65 1 5.12 64279Vj517sCOX7bkgEDp4 SFRS2 8.91 6.2 0 0 1.97 0.88 5.05 3bLQpTO7qY6IcsqcpU9.13 5 0 0.02 0.14 0.53 4.93 oVIueo8S_4lHuXrf38 9.45 3.75 0 0.08 −1.970.12 4.88 5537 T0upGOh1A5dC87MXtU PPP6C 8.7 9.12 0 0 5.6 1 4.84 3303oon0If5P1yz97_0vdA HSPA1A 7.81 11.48 0 0 7.83 1 4.83 8799fXfXV87cXRQXZ00.pU PEX11B 8.28 11.42 0 0 7.78 1 4.83 7561lKUJ_nTlzLVJH_opQ ZNF14 9.65 3.78 0 0.08 −1.91 0.13 4.75 4410873_v4Ax_iKWruunRl7o LOC441087 9.64 3.92 0 0.06 −1.67 0.16 4.69 9698rtyX5WJ.XxDSJV3Rfs PUM1 8.36 10.48 0 0 6.94 1 4.67 235316p_X8jaueM_Xv1yw6k MMD 8.74 8.14 0 0 4.49 0.99 4.64 201895EujpL.ey.6oe6yd_j4 C4orf34 8.13 14.77 0 0 10.22 1 4.63 549433..iEi3R1JerhIkIdY C21orf55 9.53 5.76 0 0.01 1.32 0.79 4.61 6421BI_6Dq7CEPrKq4C6v4 SFPQ 8.42 6.19 0 0 1.97 0.88 4.56 rOj_KbuCgz916dxzQw8.34 10.12 0 0 6.6 1 4.56 95Lo1SR.qKUKaujTcI 9.92 4.66 0 0.02 −0.41 0.44.55 8353 Qeg9LG4ofofrqRIOTc HIST1H3E 8.03 13.27 0 0 9.22 1 4.52 196968EJ0RR5LUl6uEiYB1N0 C15orf51 9.93 4.83 0 0.02 −0.14 0.47 4.51 6541EdV._eEEe7E_FH1xTE SLC7A1 8.53 4.41 0 0.03 −0.82 0.31 4.5 9991uJEnKJd4T7eu.xut70 ROD1 8.62 4.82 0 0.02 −0.15 0.46 4.5 91746TPXO9LJuvjnPvyX1XU YTHDC1 8.28 11.2 0 0 7.59 1 4.48 1979BslHrteoP3r6P65Xgc EIF4EBP2 8.6 10.02 0 0 6.51 1 4.43 QJdcrnqPEruJZ7vSUM9.27 3.56 0 0.1 −2.3 0.09 4.42 55954 W1_p0JzXVF0l3QMnqE ZMAT5 8.87 3.570 0.1 −2.28 0.09 4.39 63905 o1SeiQ915dJfeLJ6hw MANBAL 9.83 3.89 0 0.07−1.72 0.15 4.36 10776 ldJER5S31UM3t13Q9U ARPP-19 8.66 5.89 0 0.01 1.520.82 4.33 523 9jjkvez8_57t61wuiU ATP6V1A 8.08 7.98 0 0 4.31 0.99 4.32644316 uIjqv_dLQUlSnouS64 FLJ43315 9.62 4.53 0 0.03 −0.63 0.35 4.3 5870x1XT6BAF8B6iBfLVd0 RAB6A 8.49 4.03 0 0.06 −1.48 0.18 4.28 66376p70kiAVO13dTKl7.E SNRPG 8.8 4 0 0.06 −1.54 0.18 4.22 92014lXJ52op4pKIN398PpQ MCART1 8.97 4.14 0 0.05 −1.29 0.22 4.22 4591KlQBL5QH_U_515P7v4 TRIM37 7.83 17.14 0 0 11.57 1 4.2 NXbzUdlml1QLnqPMjs9.96 3.91 0 0.07 −1.69 0.16 4.19 64081 QovYhSXqQRJiB_3c8A PBLD 9.01 4.030 0.06 −1.47 0.19 4.18 KOh3bXtFSnouSaZDdo 9.79 4.1 0 0.05 −1.35 0.214.16 6612 KTL3lz7X1eKdT55_uk SUMO3 8.85 3.67 0 0.09 −2.1 0.11 4.13TC6K_S4jZhHkdyXqSw 9.21 3.63 0 0.09 −2.18 0.1 4.12 56951xJ6CCltTXt36mhLsf0 C5orf15 8.35 9.64 0 0 6.13 1 4.1 Kr6LkumY3SeHklXn1Q9.16 3.75 0 0.08 −1.96 0.12 4.1 Tnzt7MoO0S5COeclSk 8.61 5.23 0 0.01 0.510.62 4.09 11254 WkSP0Ei5_kz7KudDro SLC6A14 7.8 10.79 0 0 7.23 1 4.07161291 0knRyVFXXc.6sIg.HE TMEM30B 7.67 12.77 0 0 8.85 1 4.050ug6VOXstUnHainSSQ 9.47 3.96 0 0.06 −1.6 0.17 4.04 6431Wlx.h.xvVPXu8UX11Y SFRS6 8.76 4.25 0 0.04 −1.09 0.25 4.04cm4lFmVpfyDn8P93SI 8.83 4.14 0 0.05 −1.29 0.22 4.03 388TkrTkRL.jAqSwQs_qU RHOB 8.24 14.28 0 0 9.91 1 4.01 3423KO51fUnriKKLyJ62.4 IDS 9.77 5.98 0 0.01 1.66 0.84 4 6009WpIADoapJ9EKQt9Odo RHEB 8.76 6.36 0 0 2.2 0.9 4 3fz69f76kQGfSfhqtU 7.9211.79 0 0 8.09 1 3.98 22856 EEbT6Knmz_wMl450.o CHSY1 8.33 4.95 0 0.020.06 0.52 3.98 55322 3eF5TAxUCMwHt9RZVU C5orf22 8.79 4.79 0 0.02 −0.20.45 3.98 9349 61JLrT2EGAtMWyAI6Y RPL23 8.86 4.09 0 0.05 −1.38 0.2 3.95cqP908kSr1CVAW4I6I 8 11.93 0 0 8.2 1 3.95 83990 NqPEruJRLl6VPfi.4w BRIP18.79 3.79 0 0.08 −1.9 0.13 3.94 7358 EVK3TX0oP_S9DiCKiE UGDH 8.1 8.26 00 4.63 0.99 3.93 upama6dEf0ztde_8wk 8.65 4.22 0 0.04 −1.15 0.24 3.9211177 cX4LnsUuenkrPC1C.M BAZ1A 7.95 8.35 0 0 4.74 0.99 3.86 64589507pmZey1Scf6KeKQig LOC645895 10.25 3.65 0 0.09 −2.15 0.1 3.85xeo8Sk4FFmXpVb3Xx4 8.83 3.73 0 0.08 −1.99 0.12 3.84 6120c_d7RUp4LkukS0qVPk RPE 9.63 4.22 0 0.04 −1.15 0.24 3.8 1129cjfMdel0LjXXl0t1AI CHRM2 9.11 4.13 0 0.05 −1.31 0.21 3.79 10513h4ZBUbsHtJaleLDZ8 CEBPB 8.43 8.96 0 0 5.42 1 3.78 81671Tp55MecDpF3qPpcXqg TMEM49 8.22 13.43 0 0 9.33 1 3.75 360607riWI_RT5ncl6kEEk IL18 8.99 5.43 0 0.01 0.82 0.69 3.74xoleNeUeR1JWphIuIU 9.16 3.84 0 0.07 −1.81 0.14 3.71 56943rh_ungNHUApIlesXhI ENY2 8.7 6.15 0 0.01 1.9 0.87 3.68 374900HAuNld.pdUC56r8Sn4 ZNF568 9.12 3.62 0 0.09 −2.19 0.1 3.66 6789B4rSS.s4hMn11PlVHU STK4 8.41 6.58 0 0 2.51 0.93 3.64 23471rvRN_9VP3R_7RSe.uU TRAM1 8.54 5.47 0 0.01 0.88 0.71 3.64NCtOUeR1JenhLiHe3Q 8.99 3.63 0 0.09 −2.18 0.1 3.63 2625rkl7nirJLs4nFJuTtI GATA3 7.68 13.06 0 0 9.07 1 3.62 6202oA0kt16KJL1JKkJ9_Y RPS8 9.06 12.8 0 0 8.87 1 3.62 3jtH4VT87sokcRT6.U8.54 5.49 0 0.01 0.92 0.71 3.61 7570 fV_F33pPde53hAeJSU ZNF22 8.95 4.360 0.04 −0.91 0.29 3.58 8766 x_3fmudOO7qkRoKT54 RAB11A 8.16 7.97 0 0 4.30.99 3.56 2764 TlKkvVHj8jrUIw3T0o GMFB 8.61 4.74 0 0.02 −0.27 0.43 3.55618 rooyfiVKL2IXl6kMyY BCYRN1 8.83 4 0 0.06 −1.53 0.18 3.54 25862N1ycfqKeK6iD50JUos USP49 8.4 4.34 0 0.04 −0.95 0.28 3.52 8763TvI.5C3EDid_QSB0SU CD164 8.26 11.12 0 0 7.52 1 3.51 8323KSxf3SE.7IPT9pJ0co FZD6 8.1 7.38 0 0 3.57 0.97 3.5 100920YsncAQFF4UIqC4n7k ARPC5 8.31 7.17 0 0 3.31 0.96 3.47 221786fuzJSu66fGXsNUkuog C7orf38 9.43 4.39 0 0.04 −0.87 0.3 3.46 259783oojO7BevD_o66E.6k CHMP2B 8.26 6.28 0 0 2.08 0.89 3.44 6882ugdep8LhXVF0t14snI TAF11 8.71 3.55 0 0.1 −2.31 0.09 3.43 9584EbiLespAkt4gIDKA5I RBM39 8.51 4.24 0 0.04 −1.12 0.25 3.43 4886Zog_qRUSg4IiAknVwc NPY1R 7.84 18.81 0 0 12.37 1 3.43 lz3dA9fim4lFmVJe108.72 3.59 0 0.1 −2.25 0.1 3.42 57092 uopJ9Ie.z66yefnit8 PCNP 8.44 5.57 00.01 1.04 0.74 3.42 BUeCUsqeDFU7KBIdJE 7.74 22.2 0 0 13.71 1 3.4 139886Kz54_x6_fvh7HPSOk SPIN4 8.15 8.13 0 0 4.48 0.99 3.4 8161ESkXp4u56LijfgSAfU COIL 8.12 5.9 0 0.01 1.53 0.82 3.37 551533TT_J5fTHr9dJfX0l4 SDAD1 8.32 5.33 0 0.01 0.68 0.66 3.36 6613Kf.7Gye8TsqQ3t.Cyo SUMO2 9.7 7.45 0 0 3.66 0.97 3.35 114908oqeOni_zvHB_leHr7k TMEM123 9 3.61 0 0.09 −2.22 0.1 3.33 250T3OZey1ScVKKeCSjDY ALPP 9.07 4.02 0 0.06 −1.5 0.18 3.33 10890BKn_Vf97C3fqNe7IJ4 RAB10 8.11 7.56 0 0 3.8 0.98 3.33 rm2n1SLnqPErtJR5nQ8.89 3.79 0 0.08 −1.9 0.13 3.31 7019 HlBzpe6NA1JeeXn.zo TFAM 8.3 7.02 00 3.11 0.96 3.28 286148 N5KS7F0r4d7E3gy4tE DPY19L4 8.19 6.92 0 0 2.970.95 3.27 9167 fSofivk._JOq5KJf3o COX7A2L 8.12 12.25 0 0 8.45 1 3.2455319 EIrK.z_6IiL4I8qBS4 FLJ11184 8.05 6.6 0 0 2.54 0.93 3.22 54407BvIpQQ9yzp_kCLnEU SLC38A2 8.4 6.37 0 0 2.22 0.9 3.21 10276ZqbssL7IKdiqG6Hz_U NET1 8.25 4.9 0 0.02 −0.02 0.5 3.16Wt097RUr6LkuoIn69E 9.01 3.64 0 0.09 −2.16 0.1 3.16 7325EiHe.NHJfe1dWSCHvo UBE2E2 8.51 4.73 0 0.02 −0.29 0.43 3.14 6138QrxUd7UdUynEgAtEJk RPL15 8.18 5.64 0 0.01 1.14 0.76 3.13o57uHOPXCP1KnwqcH0 8.06 9.44 0 0 5.93 1 3.12 4893 Hr.Uil7.qn9UogI4B4NRAS 8.34 4.51 0 0.03 −0.66 0.34 3.12 55142 QLTjRlHmcSXqYRLCFc CEP278.28 3.66 0 0.09 −2.12 0.11 3.11 114882 NXkuwsSRHtA9.18K5E OSBPL8 7.857.98 0 0 4.3 0.99 3.07 136051 Z6ijZeJUqK0KeS4kOM ZNF786 8.41 3.73 0 0.08−2 0.12 3 79693 0C3Sunm7rp05ew1QT0 YRDC 9.1 5.07 0 0.02 0.26 0.57 2.9980790 339VXWtUx9Ekd65qCA CMIP 8.57 4.06 0 0.05 −1.42 0.19 2.96 3646uJK0inXB6kHQj3p9x4 EIF3E 8.59 3.88 0 0.07 −1.73 0.15 2.95 29887lsC9OU1KT8ImNdNX0k SNX10 7.85 6.55 0 0 2.47 0.92 2.95 830WH4ug1.XRsdUSG3qXo CAPZA2 8.18 9.55 0 0 6.05 1 2.94 54602W6TMoe6re7uy4i7slE NDFIP2 8.41 4.59 0 0.03 −0.53 0.37 2.94 6477lv.m6i7uXm6u7m7_r8 SIAH1 9.8 4.44 0 0.03 −0.78 0.31 2.92 169200uXr46X666D.v0lIpx0 TMEM64 7.92 11.93 0 0 8.2 1 2.91 441454lrI4IKoICQmpJ4I44o LOC441454 7.98 4.32 0 0.04 −0.98 0.27 2.91 22934Zeqv30z1576CS_FIDk RPIA 8.43 3.61 0 0.09 −2.21 0.1 2.88 7178ihNxCNaiNmhq_5eiug TPT1 8.11 6.04 0 0.01 1.74 0.85 2.88 201965E7Kr3rjrrF3zxfOwBE RWDD4A 8.85 5.83 0 0.01 1.43 0.81 2.86 51068BrKgPKvS.NHoT0opC0 NMD3 7.84 10.9 0 0 7.33 1 2.86 80777fdT.UAsIh1JOl97_VY CYB5B 8.26 4.68 0 0.02 −0.37 0.41 2.84flNOuHtOvcSA5XU7tU 8.02 4.73 0 0.02 −0.3 0.43 2.82 11529403JNI0NUINTSQXSFBU PCMTD1 8.09 6.44 0 0 2.32 0.91 2.8 1408909s.Lqg6Ai_V_QsOCU SFRS12 8.18 5.07 0 0.02 0.26 0.56 2.78 84061BjOAPp6n66dOXutcnE MAGT1 8.43 3.57 0 0.1 −2.29 0.09 2.77 2618xU75QpS3gNep0LjXXk GART 8.85 3.97 0 0.06 −1.58 0.17 2.76 6902rjjjVI_UmSvoJZM.o0 TBCA 8.22 7.29 0 0 3.45 0.97 2.74 WdS75zuQjXd_if.5Mk8.25 5.93 0 0.01 1.58 0.83 2.73 6670 KkuP.NQ379QAU7dUqU SP3 8.24 5.25 00.01 0.54 0.63 2.73 3QAgAvknv_E94OfcI 8.32 4.63 0 0.03 −0.46 0.39 2.73T3rvQHVwCKluPrqpSo 10.1 −3.88 0 0.07 −1.74 0.15 0.37 10787QhwfU65XvpPJHFPsV4 NCKAP1 8.13 5.27 0 0.01 0.58 0.64 2.72 26065TiQsU6QxO7Ie_iO1ak LSM14A 8.32 7.6 0 0 3.85 0.98 2.71 340252Hoile8vx.0z4uOTiso ZNF680 7.9 5.37 0 0.01 0.74 0.68 2.68 262Bone.4oUOfCuh.vbAQ AMD1 8.4 3.68 0 0.09 −2.1 0.11 2.68 83930NuzpeC76H5AKoICg_Y STARD3NL 8.31 5.56 0 0.01 1.03 0.74 2.67 81688lf1UL5z7CLPeebujks C6orf62 8.38 4.25 0 0.04 −1.1 0.25 2.67 8540306QoKyj94B0pfBQyvo EAF1 8.17 4.46 0 0.03 −0.74 0.32 2.66Tlmcdek7o0UIxD9614 7.97 7.46 0 0 3.67 0.98 2.65 51020 HSgmtOAuU6OBHorpLkHDDC2 8.1 7.55 0 0 3.78 0.98 2.65 648852 Hp05ew1ST_rrUtPGNE LOC6488528.34 3.6 0 0.1 −2.24 0.1 2.6 7324 Newpugyi_dLo_vc77o UBE2E1 8.12 3.71 00.08 −2.04 0.12 2.6 10209 oidAild8WcmK4yhN6c EIF1 8.19 6.06 0 0.01 1.770.85 2.59 51388 0SKUYTAD0tX_19VuXU NIP7 8.03 9.45 0 0 5.94 1 2.58 23658Bnr16KIKF4LuDi.X4c LSM5 8.37 6.65 0 0 2.61 0.93 2.58 134266ip0d0fgiqN_u_yx_h4 GRPEL2 8.16 4.88 0 0.02 −0.04 0.49 2.58 53938lkpP.i6XjxM9dUSQtY PPIL3 8.11 6.84 0 0 2.87 0.95 2.58 10724BRK4e4BI5V635.TR3I MGEA5 7.87 6.79 0 0 2.79 0.94 2.57 9554BMozoilXp9OIECkpUo SEC22B 7.99 15.2 0 0 10.49 1 2.57 1105Qv9W.zupDDtA7nOSUo CHD1 7.71 6.65 0 0 2.61 0.93 2.57 54477Qf3a0j5DtJLx5RHXtI PLEKHA5 8.28 5.28 0 0.01 0.59 0.64 2.57 220213rpMDt6JQX6S8ySiBHs OTUD1 8.13 6.79 0 0 2.79 0.94 2.56 5359ZlKBADSi7rLo8uAt10 PLSCR1 7.77 10.02 0 0 6.51 1 2.56 803063qL.LbKXzjDxVmuu7I MED28 7.92 8.69 0 0 5.12 0.99 2.54 3344THlLI4UtELgUfdL5Q0 FOXN2 8.03 5.94 0 0.01 1.59 0.83 2.54 469806s0AQhA570qAgvpCc NDUFA5 7.87 5.21 0 0.01 0.48 0.62 2.53 58517KEReiKE.gBHvfFdgV4 RBM25 7.98 6.25 0 0 2.05 0.89 2.52 51192oE2VfefS7gKUbgjnmk CKLF 8.52 3.89 0 0.07 −1.73 0.15 2.52 84515rS4lENEUNHkdSXqQwI MCM8 8.71 3.86 0 0.07 −1.77 0.15 2.51 234786.U5SL_7qamTuRRIuQ SEC11A 8.07 5.32 0 0.01 0.65 0.66 2.5T6HQktdUXyXXgyeDEo 8.21 4.96 0 0.02 0.08 0.52 2.5 10628fSUyR.vR7Xu0iR4nUU TXNIP 8.22 5.98 0 0.01 1.65 0.84 2.49 51643NovrfJZ5KJX3.e6PTQ TMBIM4 8.06 7.05 0 0 3.14 0.96 2.49 81853BVxIrriTsE4nz4hTTI TMEM14B 8.2 3.98 0 0.06 −1.57 0.17 2.47 27020iqfBe4fwwnoEtR4OrM NPTN 8.2 4.77 0 0.02 −0.24 0.44 2.46 8661lrdPglBEgfnnu..fS4 EIF3A 7.79 4.51 0 0.03 −0.67 0.34 2.453U8Xo7.7Ueoikn66KU 8.34 3.67 0 0.09 −2.1 0.11 2.45 51430WtSOIkiMS4gPO43u74 C1orf9 8.06 3.72 0 0.08 −2.02 0.12 2.44 126567ihtX7SVv5RE_9d_1Ko FAM148C 9.91 −3.78 0 0.08 −1.91 0.13 0.41 51065itSvnEI0Ua.0lOdIS4 RPS27L 8.06 8.91 0 0 5.37 1 2.43 64065oep3NMyEp94y.kHsJI PERP 8.05 3.86 0 0.07 −1.77 0.15 2.43 130355cdeeAghJHeAknoNlLg LOC130355 8.23 8.38 0 0 4.78 0.99 2.42 7555fqCL4tIUsJW16vX4E4 CNBP 7.96 4.83 0 0.02 −0.14 0.47 2.42 848393_IUl6uESQhVN1EBv8 RAX2 8.36 4.84 0 0.02 −0.12 0.47 2.39 511230TVTvweER6qdL7uew4 ZNF706 7.78 6.85 0 0 2.87 0.95 2.38 284996NV.Pl0.fuGX76oqA3s RNF149 7.97 6.43 0 0 2.31 0.91 2.37 84928TFuzS7yO5NW.7T1dIc TMEM209 7.87 8.41 0 0 4.81 0.99 2.37 54830oJfvfK.oEt63Xu.Tv0 NUP62CL 7.93 5.78 0 0.01 1.36 0.8 2.37 2353cVLhH0iJ6y8sk74lKU FOS 7.81 6.76 0 0 2.76 0.94 2.37 8299gCu.udb.v3nSwzLQk CAPZA1 8.32 5.27 0 0.01 0.57 0.64 2.37 175ud3s4QdxIL7mbn90kk AGA 7.76 6.85 0 0 2.88 0.95 2.36 54965ZUnD6Crimoo2fgXqKY PIGX 8.05 3.89 0 0.07 −1.73 0.15 2.36 7879T9.r6BXpL3nV9co3lU RAB7A 7.82 8.29 0 0 4.68 0.99 2.35 81542WQ.ew7Vff3Kd757uDU TXNDC1 8.12 4.71 0 0.02 −0.34 0.42 2.34 6659BE4SkcobeX.wpL1vCo SOX4 8.41 7.25 0 0 3.41 0.97 2.34 142uFAn28g7eXx6.VSoKA PARP1 8.15 3.95 0 0.06 −1.61 0.17 2.32 58155Bo.eJO5IetycvUoHrk PTBP2 7.95 6.96 0 0 3.02 0.95 2.32 513173tLitW4t.uLX7tNvak PHF21A 8.07 4.7 0 0.02 −0.34 0.41 2.31 29994E7BR7v83Hu77rpe_ik BAZ2B 7.67 5.43 0 0.01 0.83 0.7 2.31 1968391X5316XgEagFItAI EIF2S3 8.47 4.07 0 0.05 −1.42 0.2 2.31 57160p77i30kV1TsXzNXd4 PSMD10 7.76 9.73 0 0 6.23 1 2.3 9662clf.Luzyjup6.n.cUU CEP135 8.1 3.7 0 0.08 −2.05 0.11 2.29 4154lNSX0dSevADvkfNJBU MBNL1 7.99 6.13 0 0.01 1.88 0.87 2.29o0jMIgt09l.t_x97vc 8.17 6.82 0 0 2.83 0.94 2.28 79738 Ql3u3Sd7vJc7vyqKv8BBS10 7.97 6.98 0 0 3.05 0.95 2.27 7342 BX_f27hRO.3sUtHqgI UBP1 8.085.57 0 0.01 1.04 0.74 2.27 23271 Zr9OhHviQ7EuzrufF4 CAMSAP1L1 7.76 6.660 0 2.61 0.93 2.26 11112 E6HW0QzrKM1dFB1YR0 HIBADH 8.06 4.27 0 0.04−1.07 0.26 2.26 51014 rrSTqTOwDtf96_Xdzk TMED7 8.22 5.04 0 0.02 0.210.55 2.25 27075 WukXoPx7PT7ake1Huk TSPAN13 8.04 8.59 0 0 5.02 0.99 2.2423011 xjq9LrOJIoIjVIyyUs RAB21 7.91 5.66 0 0.01 1.17 0.76 2.24 58516NVfUXd.l7KOx7Oy05E FAM60A 7.8 6.64 0 0 2.59 0.93 2.23 Wu.75CAC_Se.74T3g47.9 4.06 0 0.05 −1.43 0.19 2.21 5093 3gqTquScgS7K9XQwVc PCBP1 7.88 6.790 0 2.79 0.94 2.21 1871 T4goqM4KCOn5IsLauk E2F3 8.3 3.68 0 0.09 −2.10.11 2.2 255919 T1zl9FIMH6i65SAci0 TMEM188 8.36 6.16 0 0.01 1.91 0.872.2 6259 H_Rcgy5zkSJq5_L77Y RYK 8.05 3.69 0 0.08 −2.08 0.11 2.2 6767TuyL3X92A_Uu7H6fB0 ST13 7.64 5.61 0 0.01 1.11 0.75 2.2 839400a7sqouuT0.jrFCgkk TATDN1 7.57 7.79 0 0 4.09 0.98 2.19 29978EuSXgo0uyw5SgLn.xc UBQLN2 7.87 6.99 0 0 3.07 0.96 2.18 23608NHao516.tTcef49fo0 MKRN1 7.67 7.92 0 0 4.23 0.99 2.18 54534uqR7Qfq.CEooT5C9EU MRPL50 7.97 6.1 0 0.01 1.84 0.86 2.17 7803ifq.oxXy6jjsDIpycU PTP4A1 8.43 5.89 0 0.01 1.52 0.82 2.17 79752lTulCXJNOiUgLMl_e0 ZFAND1 8.27 10.19 0 0 6.67 1 2.17 865Efl8JxSPn.lFPpTHu4 CBFB 8.17 5.44 0 0.01 0.85 0.7 2.16 57122xnSItd3DnXIUqH4VPI NUP107 7.93 7.15 0 0 3.28 0.96 2.15Ngq1B7hzIHur81.Q14 8.09 6.39 0 0 2.24 0.9 2.15 10577 NJ1q6evdLr7dO3f.e0NPC2 8.32 4.37 0 0.04 −0.89 0.29 2.14 55529 9oNJ3ZHlTf5L.gAgPk TMEM55A8.08 5.65 0 0.01 1.17 0.76 2.13 27430 ul15.zJL86okfgIm7s MAT2B 8.03 4.10 0.05 −1.35 0.21 2.13 653573 Bk9InECgygLKsu_j3o GCUD2 7.96 4.77 0 0.02−0.23 0.44 2.12 KZG_akiZCkxFIAZ7Xs 7.99 10.51 0 0 6.97 1 2.12uuhgjOlTXIgfUzEfgI 8.26 6.5 0 0 2.4 0.92 2.12 8545 ZS9NP658t.sKnd7r_ECGGBP1 7.96 10.65 0 0 7.1 1 2.12 80213 WUlQOy3l_ALf0nuHko TM2D3 7.758.34 0 0 4.73 0.99 2.12 54928 95TfnP9P9Xugjk6_TU IMPAD1 7.72 4.35 0 0.04−0.93 0.28 2.12 10049 EXn.T7t4DuJRsu2l54 DNAJB6 8.01 5.95 0 0.01 1.610.83 2.12 663 QnO7Uqz51Xi7M4ueLI BNIP2 7.93 4.89 0 0.02 −0.03 0.49 2.11387 NqbdUs8V6OMoPh1puQ CREBBP 8.15 4.06 0 0.05 −1.43 0.19 2.1 54665lP5emhz_b7ul8v78_E RSBN1 7.71 6.78 0 0 2.78 0.94 2.1 642073qqOq7P_Qv7iqAO.4 C14orf4 7.83 5.15 0 0.01 0.39 0.6 2.1 90799rV1c4pSH4wyyuCveik CCDC45 7.83 7.24 0 0 3.39 0.97 2.1 360023Wi7p5SAMMQB6k.J71E ZBTB41 7.65 6.04 0 0.01 1.75 0.85 2.09 31813.X_koK7fnkrBw4ILo HNRNPA2B1 8.01 5.69 0 0.01 1.22 0.77 2.08 7082ohCqS66.3vf3pzk.gA TJP1 8.47 4.59 0 0.03 −0.52 0.37 2.07 64431EafR6Ev9fIKy.7uHuE ACTR6 7.6 7.6 0 0 3.85 0.98 2.07 9445KqFEuHz_y_8vlXnFcs ITM2B 7.68 9.54 0 0 6.03 1 2.07 3183ZTw9M_VZly1T.R9f4Y HNRNPC 8.11 4.64 0 0.03 −0.45 0.39 2.07 64968EDF16j7ictPSXuwU7o MRPS6 8.27 3.77 0 0.08 −1.93 0.13 2.06 51582WrkH_LX6fhzEpfgfTo AZIN1 7.76 5.75 0 0.01 1.31 0.79 2.06 65966qPJWck8okvqC8XrI0 HLTF 7.55 5.94 0 0.01 1.6 0.83 2.06 64746ZVJ0yu9Me8TUgT_0p0 ACBD3 7.76 5.4 0 0.01 0.78 0.69 2.06 50808WunPH_9_tfRKl51NUU AK3 7.89 7.68 0 0 3.94 0.98 2.05 57182xo6ueiOV5fnz_.e6qM ANKRD50 7.7 8.77 0 0 5.21 0.99 2.05 7852QpKF7pQvfL57O3brKE CXCR4 8.17 8.41 0 0 4.81 0.99 2.05 85319XkaCEIiyXdS.SQWco CSDA 8.26 5.26 0 0.01 0.56 0.64 2.05uop775UlKlnk.4QT9Q 8.7 5.02 0 0.02 0.18 0.54 2.04 38383JNewMBPQtRX.fh9AA KPNA2 7.84 4.04 0 0.06 −1.45 0.19 2.04 4144i65p6U6ICeH6eu6xIg MAT2A 8.1 4.03 0 0.06 −1.48 0.18 2.04 9006nngsu.KNdTpLy4Owg CCNG1 8.08 4.78 0 0.02 −0.21 0.45 2.03 10627ZPwXFJX3VUMHutzEi0 MRCL3 7.83 7.15 0 0 3.28 0.96 2.03 5412ll4OOJc7V5cEeu3R00 UBL3 7.66 10.57 0 0 7.02 1 2.03 1657oNuQwUzmHP_U6IDeEk DMXL1 7.66 5.68 0 0.01 1.21 0.77 2.02 568890N70r67FuwLqjqsAus TM9SF3 7.88 4.12 0 0.05 −1.32 0.21 2.01 291163k.6CetJySv96jtqIU MYLIP 7.88 6.61 0 0 2.54 0.93 2.01 10797NqwsZB8f9RQIHtJJ5c MTHFD2 7.72 6.25 0 0 2.04 0.88 2.01 10728Hd8k6KGCAnsT75_It4 PTGES3 8.06 3.98 0 0.06 −1.56 0.17 2.01 90390KanpUXb.nLgiKYgPng MED30 7.87 9.92 0 0 6.41 1 2.01

TABLE A4 Genes Overexpressed in MDA MB 231 cells (Top Genes of Interest,Fold = MDA.3A2/MDA.IgG) LOCUS PROB OF FOLD LINK ID ID GENESYMBOL AVEEXPRT P. VALUE ADJ. P. VAL B DIFF EXP CHANGE 928 rWSgWYjrci0nxNXiSg CD9 8.7911.38 0 0 7.77 1 8.04 5757 QQ3z1iT1LB..uzsfJ4 PTMA 9.07 7.55 0 0 3.620.97 7.15 7325 EiHe.NHJfe1dWSCHvo UBE2E2 8.51 7.85 0 0 4 0.98 6.67 10983oioTn1X7UX_SXv3tOw CCNI 9.9 6.59 0 0 2.31 0.91 6.24 506159uFU4ntnk3904JGqBo IL21R 9.95 −5.21 0 0 0.23 0.56 0.17 51192oE2VfefS7gKUbgjnmk CKLF 8.52 7.45 0 0 3.49 0.97 5.86 102503Qf0iXfs.oKegqVIf4 SRRM1 8.89 6.99 0 0 2.87 0.95 5.74 6789B4rSS.s4hMn11PlVHU STK4 8.41 8.85 0 0 5.19 0.99 5.67 22809e1epSSoXeCX3_6X.8 FKBP1A 8.74 5.49 0 0 0.67 0.66 5.6291epSSoXeCX3_6Xz.8 8.67 5.5 0 0 0.7 0.67 5.53 0u8YIQMtNHfU.4qpSo 10.05−5.55 0 0 0.77 0.68 0.18 5376 xyJ_nq3Ke97l1Ch7ek PMP22 8.64 7.38 0 0 3.40.97 5.51 WiCeQtLnkLSwQPd.6o 10.21 −5.08 0 0 0.01 0.5 0.19 5146oV7hzggDMz5yVADVKo PDE6C 10.28 −5.18 0 0 0.18 0.54 0.19 805Kvvgu6L7B3m6HOhLQQ CALM2 9.75 5.38 0 0 0.5 0.62 5.08 235316p_X8jaueM_Xv1yw6k MMD 8.74 8.52 0 0 4.81 0.99 4.99 85319XkaCEIiyXdS.SQWco CSDA 8.26 11.78 0 0 8.13 1 4.99 26511WULO_39Q65fn653Xro CHIC2 8.09 10.44 0 0 6.88 1 4.95 98020Lt45pR09p1Ug9ch6s DAZAP2 9.11 6.05 0 0 1.52 0.82 4.93T3rvQHVwCKluPrqpSo 10.1 −6.14 0 0 1.66 0.84 0.2 7570 fV_F33pPde53hAeJSUZNF22 8.95 5.39 0 0 0.51 0.62 4.83 481 unu3iN6N5U0f6cuEqc ATP1B1 9 5.030 0 −0.07 0.48 4.82 144195 TVKHn3g55x_P3901Rk SLC2A14 9.01 −7.66 0 03.76 0.98 0.21 3jtH4VT87sokcRT6.U 8.54 6.68 0 0 2.44 0.92 4.77rmU1_i8gtIlEgfEoKo 9.87 −5.27 0 0 0.32 0.58 0.21 23471rvRN_9VP3R_7RSe.uU TRAM1 8.54 6.58 0 0 2.31 0.91 4.73 56943rh_ungNHUApIlesXhI ENY2 8.7 7.32 0 0 3.31 0.96 4.71 o0jMIgt09l.t_x97vc8.17 12.79 0 0 8.98 1 4.69 cV.XdXSD_7_eXc37.8 8.15 5.55 0 0 0.76 0.684.64 54890 Wd0qlIHX_Um6P3QtqE ALKBH5 8.34 4.93 0 0 −0.22 0.44 4.63 59113zSS37vJHqwn8PtXyU RAP2A 8.55 3.59 0 0.02 −2.55 0.07 4.63 54499uYd0KR7s5XkL6e3OJM TMCO1 8.53 8.59 0 0 4.9 0.99 4.62 56675ulCHVOeXT_z0JfwSio NRIP3 9.95 −5.17 0 0 0.17 0.54 0.22QdMemVgEEgZBADdUqo 9.73 −6.04 0 0 1.52 0.82 0.22 23204ZKnvriJIfiuOMvpd60 ARL6IP1 8.7 6.65 0 0 2.4 0.92 4.55 1979BslHrteoP3r6P65Xgc EIF4EBP2 8.6 10.18 0 0 6.62 1 4.53 57092uopJ9Ie.z66yefnit8 PCNP 8.44 6.85 0 0 2.68 0.94 4.53 KEU0k28Q8Md.COAd6o10.01 −5.13 0 0 0.09 0.52 0.22 81929 oOeEeUF1LNdFdkhjN0 SEH1L 8.28 6.180 0 1.72 0.85 4.53 BneDXnVKlABNhcgoKo 9.76 −5.46 0 0 0.63 0.65 0.22 934961JLrT2EGAtMWyAI6Y RPL23 8.86 4.47 0 0.01 −1.01 0.27 4.49 80777fdT.UAsIh1JOl97_VY CYB5B 8.26 6.73 0 0 2.51 0.92 4.48 10513h4ZBUbsHtJaleLDZ8 CEBPB 8.43 10.06 0 0 6.5 1 4.46 5376BUGRWL_7_KUV4o2oSc PMP22 7.86 8.87 0 0 5.22 0.99 4.45 4938563GcqHr1KlETMUA3lTE CISD2 8.94 7.77 0 0 3.9 0.98 4.4 1127149o3uRKHkqfXTfUSf6o TUBA3E 9.84 −4.69 0 0 −0.63 0.35 0.23 10933355S7.Q46EEioznsi4 MORF4L1 8.99 6.24 0 0 1.81 0.86 4.31 5094c12iGrpOqJJyBDkj00 PCBP2 8.67 7.78 0 0 3.91 0.98 4.29 83930NuzpeC76H5AKoICg_Y STARD3NL 8.31 8.24 0 0 4.48 0.99 4.29 1454KUX94ool6LSp6v_jwU CSNK1E 8.01 8.16 0 0 4.39 0.99 4.26 10209oidAild8WcmK4yhN6c EIF1 8.19 9.17 0 0 5.56 1 4.23 7534rpFefX_fk1RIc.V01w YWHAZ 9.06 4.15 0 0.01 −1.55 0.17 4.17 6205K2KmjXd6brhQjgjkig RPS11 8.16 6.48 0 0 2.16 0.9 4.15 lDUU4IgCSggvQnJV6o9.9 −5.22 0 0 0.25 0.56 0.24 960 T4Ue8_8f4f9IkRX13o CD44 8.07 5.1 0 00.05 0.51 4.12 81688 lf1UL5z7CLPeebujks C6orf62 8.38 6.13 0 0 1.65 0.844.12 54602 W6TMoe6re7uy4i7slE NDFIP2 8.41 6.01 0 0 1.47 0.81 4.09 56994Bo1HMkpFLt_0XodRMo CHPT1 8.17 7.09 0 0 3.01 0.95 4.09 2357600nHeBI8cKU3XTdwqI DDAH1 8.53 5.21 0 0 0.23 0.56 4.09 HOIEVCRGCPeSm7Kqho9.54 −5.49 0 0 0.67 0.66 0.24 30968 N42LQji8uiep_lKi3o STOML2 8.36 4.610 0 −0.76 0.32 4.08 2811 xt9EESkRD9LVJQJIKo GP1BA 9.91 −5.25 0 0 0.290.57 0.24 7027 TFXnpoyQh3ui.vS6xo TFDP1 9.31 3.47 0.01 0.02 −2.75 0.064.08 125144 WUCkSlC_yf7V_U05UE C17orf45 8.82 4.4 0 0.01 −1.12 0.25 4.053ndP7d.E5d9HEi3qJc 8.95 −8.34 0 0 4.59 0.99 0.25 1968 391X5316XgEagFItAIEIF2S3 8.47 6.79 0 0 2.6 0.93 4.04 QPR6W2.xBr2_AFf.6o 9.83 −5.26 0 00.31 0.58 0.25 7402 TFkYRSRo3RorTokj0Q UTRN 8.86 −6.61 0 0 2.35 0.910.25 10285 3Svt5P767C4E00S814 SMNDC1 8.71 8.83 0 0 5.17 0.99 4.02 51187frL7o56o4geDDf5ei4 C15orf15 8.9 6.93 0 0 2.79 0.94 4.01WUQEjs7ct7.0ut3W30 7.81 15.08 0 0 10.67 1 4.01 QpA1IiEgrK.uvnqpyo 9.88−6.04 0 0 1.52 0.82 0.25 6637 6p70kiAVO13dTKl7.E SNRPG 8.8 3.84 0 0.01−2.1 0.11 3.99 56650 cCBv0Uw4V1InqAXFEI CLDND1 8.03 13.98 0 0 9.89 13.98 10577 NJ1q6evdLr7dO3f.e0 NPC2 8.32 7.92 0 0 4.09 0.98 3.98 1266lul7oT8perjk.nfXv4 CNN3 8.28 5.01 0 0 −0.1 0.48 3.95 4904QrnhBSrkogQrIUuKSA YBX1 8.91 4.43 0 0.01 −1.07 0.26 3.95KSKLCD61eV0KB0S3Ko 9.83 −5.01 0 0 −0.1 0.47 0.25 3930 rdek0gLrpv97Ho_RQoLBR 8.18 5.92 0 0 1.34 0.79 3.94 51176 Qun3e4Pl7BEy6fdZX4 LEF1 7.8529.08 0 0 16.84 1 3.93 26065 TiQsU6QxO7Ie_iO1ak LSM14A 8.32 10.45 0 06.89 1 3.93 8655 u6HuURFS41NSAQoeSU DYNLL1 8.07 15.95 0 0 11.24 1 3.91WUSEjs7ct7.0ut3U30 7.9 12.24 0 0 8.52 1 3.9 KZG_akiZCkxFIAZ7Xs 7.9918.98 0 0 12.98 1 3.9 0yK7oA6115Ei2l1I6o 9.75 −5.21 0 0 0.22 0.56 0.265292 ro67l9SNd3qnu.4kko PIM1 8.51 4.81 0 0 −0.43 0.39 3.89lt7HkOEt.q.AySf0Ko 9.84 −4.98 0 0 −0.15 0.46 0.26 23406xIilSrqh6g.CiJ6gaM COTL1 8.06 7.74 0 0 3.86 0.98 3.89 283412u_VFUJ_oJu.uXs_UKo LOC283412 9.7 −4.94 0 0 −0.21 0.45 0.26 4277HhSf37RfitV2VbRFvM MICB 8.15 6.25 0 0 1.82 0.86 3.87 139886Kz54_x6_fvh7HPSOk SPIN4 8.15 8.97 0 0 5.33 1 3.86 126567ihtX7SVv5RE_9d_1Ko FAM148C 9.91 −5.73 0 0 1.04 0.74 0.26cdxTd9OnP6TIz0v5Ko 9.87 −5.18 0 0 0.18 0.55 0.26 60 ZuropJSp8XsR4fiFL4ACTB 10.04 2.68 0.02 0.05 −4.17 0.02 3.83 64089 cy75e3vcCYFJR.9Dek SNX168.36 13.01 0 0 9.16 1 3.82 114908 oqeOni_zvHB_leHr7k TMEM123 9 4.01 00.01 −1.8 0.14 3.81 9njAklXtwAPlKdEgKo 9.76 −5.29 0 0 0.35 0.59 0.2710092 0YsncAQFF4UIqC4n7k ARPC5 8.31 7.62 0 0 3.7 0.98 3.75 9791fpizEUNKIqyeXkyiXY PTDSS1 8.35 5.51 0 0 0.7 0.67 3.74 10409oSEiVHyftROjdDlDXU BASP1 8.67 2.98 0.01 0.04 −3.64 0.03 3.74 8299gCu.udb.v3nSwzLQk CAPZA1 8.32 8.04 0 0 4.24 0.99 3.72 4410873_v4Ax_iKWruunRl7o LOC441087 9.64 3.33 0.01 0.02 −3.02 0.05 3.71 74019EXoQ.cghxD0tyUQKo CLRN1 9.65 −5.97 0 0 1.41 0.8 0.27 6629QonlKjn8So.CNEW1Tk SNRPB2 8.19 11.17 0 0 7.58 1 3.7 3_dx6HGuKOu4VTM4.09.69 3.58 0 0.02 −2.56 0.07 3.69 0IVAtI4TSsAOSntfKo 9.68 −4.75 0 0 −0.520.37 0.27 10776 ldJER5S31UM3t13Q9U ARPP-19 8.66 5.24 0 0 0.27 0.57 3.685352 uEC_Jfn31v_V.t2dc PLOD2 8.51 6.35 0 0 1.97 0.88 3.68 830WH4ug1.XRsdUSG3qXo CAPZA2 8.18 11.52 0 0 7.9 1 3.68 9617Ny6OfOXsNUuf4KlAqo MTRF1 9.47 −5.87 0 0 1.25 0.78 0.27Qv4vIeZ1OrFJM6XdKo 9.59 −5.23 0 0 0.26 0.56 0.27 51241Zeggz2KFSl_oI14XXU C14orf112 7.99 14.73 0 0 10.43 1 3.65 998Wiq65yCEhN7oOPRNd0 CDC42 8.18 9.1 0 0 5.47 1 3.65 285636Qjr9I_fl3.d.cXxKnU LOC285636 8.31 6.96 0 0 2.83 0.94 3.64 90390KanpUXb.nLgiKYgPng MED30 7.87 18.38 0 0 12.66 1 3.63 TSUId6F52K.UCp49Ko9.56 −5.65 0 0 0.92 0.72 0.28 6281 WpIDiS9nXV4wi_1Aq0 S100A10 8.11 10.050 0 6.49 1 3.62 rht79Y936v7VKLif6o 9.66 −5.13 0 0 0.1 0.52 0.28 9334urpV8N_3_Pnu5KgK7U B4GALT5 8.17 6.16 0 0 1.69 0.84 3.61ug3uVd4Rz6CQOAM26o 9.62 −5.54 0 0 0.74 0.68 0.28 30000fe56o_mWK6biPUfuyA TNPO2 8.14 4.35 0 0.01 −1.21 0.23 3.6 84522fdfiAXJLpTIgsh6s6o JAGN1 9.59 −5.06 0 0 −0.01 0.5 0.28 109599pf6lHvSrHhTS7STyo TMED2 8.77 14.08 0 0 9.97 1 3.6 u5vR7KXg54wJwU.6ro9.38 −5.96 0 0 1.4 0.8 0.28 ikBfwORQSIrCUJ3Sio 9.51 −5.61 0 0 0.86 0.70.28 22934 Zeqv30z1576CS_FIDk RPIA 8.43 4.34 0 0.01 −1.22 0.23 3.57 5917r7ps55zuCSyee06UKo RARS 9.74 −5.51 0 0 0.71 0.67 0.28 6745cXSOUqt53JNLCz8kgE SSR1 8.4 3.85 0 0.01 −2.09 0.11 3.56 7080_WFiq6EEf_SOJ66J0 C1QBP 8.09 18.35 0 0 12.64 1 3.56 6431Wlx.h.xvVPXu8UX11Y SFRS6 8.76 3.87 0 0.01 −2.05 0.11 3.56 9550uF7uCSSUl8Cy1PfnDo ATP6V1G1 8.68 9.12 0 0 5.5 1 3.55 80790339VXWtUx9Ekd65qCA CMIP 8.57 4.75 0 0 −0.52 0.37 3.55 606EoLV_U1wCUVR93cKI ACTB 9.62 3.04 0.01 0.03 −3.53 0.03 3.550VYLNK7XdM9eVXtLoE 8.12 22.02 0 0 14.39 1 3.54 51020 HSgmtOAuU6OBHorpLkHDDC2 8.1 9.77 0 0 6.2 1 3.54 2002 BpCIi6vQCHXqdF7yZ4 ELK1 8 5.61 0 00.86 0.7 3.53 7852 QpKF7pQvfL57O3brKE CXCR4 8.17 14.76 0 0 10.45 1 3.530ykhKFjnABGIOokAqo 9.43 −6.02 0 0 1.49 0.82 0.28 NSlu0jr49EqfyIrlKo 9.65−4.81 0 0 −0.43 0.39 0.28 1476 3e78KW7T0IlK62aoQE CSTB 8.8 3.88 0 0.01−2.02 0.12 3.51 faVeJCEsZ9BudCtFCk 8.29 6.18 0 0 1.73 0.85 3.5 1964xr_jAxdoTz.r63WIcU EIF1AX 7.74 10.46 0 0 6.9 1 3.5 262Bone.4oUOfCuh.vbAQ AMD1 8.4 4.67 0 0 −0.66 0.34 3.49 9991uJEnKJd4T7eu.xut70 ROD1 8.62 4.01 0 0.01 −1.8 0.14 3.49 5216ixuDqeEfqpSA72uNag PFN1 7.95 5.6 0 0 0.84 0.7 3.49 58155Bo.eJO5IetycvUoHrk PTBP2 7.95 10.35 0 0 6.79 1 3.49 fH3spPTrMFQhLUhFKo9.62 −5.2 0 0 0.2 0.55 0.29 11065 6V04FQT4y1fgRE55Yk UBE2C 7.77 20.28 00 13.62 1 3.49 55505 odbBQHfaHuJXjl._Uk NOLA3 7.75 12.13 0 0 8.43 1 3.483688 WunOQSd0XGYt8f4vLk ITGB1 8.91 3.23 0.01 0.03 −3.19 0.04 3.48 5089iqKTqWqkvd10fsB_7I PBX2 8.28 4.45 0 0.01 −1.04 0.26 3.48lk19P4S7i_0jzNSC6o 9.55 −5.59 0 0 0.83 0.7 0.29 3U8Xo7.7Ueoikn66KU 8.345.1 0 0 0.05 0.51 3.47 3knSoxPLgCkkHf14qo 9.36 −5.61 0 0 0.86 0.7 0.2923658 Bnr16KIKF4LuDi.X4c LSM5 8.37 8.7 0 0 5.03 0.99 3.46 56674KRP7ST9a264iknv4nU TMEM9B 7.95 7.36 0 0 3.37 0.97 3.45 2079or6rqfoESu7Em57LoI ERH 8.04 9.86 0 0 6.3 1 3.43 10817 3bQe4KvXuPm.JldW94FRS3 7.77 9.46 0 0 5.87 1 3.42 5537 T0upGOh1A5dC87MXtU PPP6C 8.7 7.11 00 3.04 0.95 3.42 55319 EIrK.z_6IiL4I8qBS4 FLJ11184 8.05 6.94 0 0 2.810.94 3.42 9528 BieNPnX3RdeU4x7S8U TMEM59 8.84 6.49 0 0 2.18 0.9 3.427346 TnRCUz6Vjy6x7eHRu4 TMEM97 8.09 6.26 0 0 1.85 0.86 3.39uop775UlKlnk.4QT9Q 8.7 8.57 0 0 4.87 0.99 3.39 28972 611OlTc2Wk13QuvF70SPCS1 7.83 14.5 0 0 10.27 1 3.39 9STIfB1fCVITe_oXhU 8.14 7.28 0 0 3.270.96 3.39 1808 ceSnuwk78Xvp_f7u3s DPYSL2 8.06 7.44 0 0 3.48 0.97 3.384082 BkH9RXlT.7AHktN_hc MARCKS 7.81 11.21 0 0 7.61 1 3.38 220134xjqRejB0o6qedECFE0 C18orf24 7.98 8.05 0 0 4.24 0.99 3.37 2280uinqCCq_VI4u6tIiUA FKBP1A 7.73 14.72 0 0 10.42 1 3.37 6230ua7eec91ifZDllwoYQ RPS25 8.16 7.39 0 0 3.41 0.97 3.37 8099rSCAiQVFAXBChVYEf0 CDK2AP1 9.55 3.44 0.01 0.02 −2.81 0.06 3.37 6155BVxJTneunoPhZxVZAs RPL27 7.88 7.76 0 0 3.89 0.98 3.36 TtKkQd7r2kgoEM.R6o9.49 −5.12 0 0 0.08 0.52 0.3 6qjsQDlf8E9QF43Sqo 9.4 −5.34 0 0 0.43 0.610.3 4673 lrfoO4ET7_y5zU9d14 NAP1L1 8.09 9.46 0 0 5.87 1 3.36 677l6PUrei.1DvDsBIHpE ZFP36L1 8.64 5.86 0 0 1.25 0.78 3.35upama6dEf0ztde_8wk 8.65 3.73 0 0.01 −2.29 0.09 3.35 147949iher1Df5H1P15XcP6o ZNF583 9.65 −5.31 0 0 0.39 0.6 0.3 11014Qk3tfSrnaEg98USQKQ KDELR2 8.57 9.05 0 0 5.42 1 3.34 cxU7L6icx93Tgt6oCo9.55 −5.28 0 0 0.34 0.58 0.3 7769 TfVYDkfutJJya3.v6o ZNF226 9.68 −5.33 00 0.42 0.6 0.3 139516 xXzn6VcSILjh4Sif6o LOC139516 9.64 −5.4 0 0 0.530.63 0.3 3TygusgH8DZVIv5e.U 7.88 11.86 0 0 8.19 1 3.32 91663T73f_VsrqKuqPnm1yc MYADM 7.77 11.41 0 0 7.8 1 3.32 55450KzhYQpF167cHVUCEOI CAMK2N1 7.77 11.61 0 0 7.97 1 3.32 84061BjOAPp6n66dOXutcnE MAGT1 8.43 4.19 0 0.01 −1.48 0.19 3.31 51228lcXFu7Pd_GqIjgV9J4 GLTP 8.44 5.82 0 0 1.19 0.77 3.31 53938lkpP.i6XjxM9dUSQtY PPIL3 8.11 8.64 0 0 4.95 0.99 3.3 80025iukTtSku4o.nszC_Xk PANK2 7.57 22.77 0 0 14.7 1 3.3 0CI6rfnS0FJUp6Lkus9.6 2.74 0.02 0.05 −4.07 0.02 3.3 Eh6UE0eiDid0RHl86o 9.62 −5.5 0 0 0.690.67 0.3 203547 Ty5Xhyqij_jueT9CW4 LOC203547 8.99 4.01 0 0.01 −1.8 0.143.29 1871 T4goqM4KCOn5IsLauk E2F3 8.3 5.53 0 0 0.74 0.68 3.29 234763lqi4pRQUC0vX1Re78 BRD4 8.11 9.29 0 0 5.68 1 3.27 51569xdez3g64HegkqPu3p0 UFM1 7.68 20.57 0 0 13.75 1 3.27 xt5p9it.0oN.QDqP6o9.37 −5.78 0 0 1.12 0.75 0.31 134266 ip0d0fgiqN_u_yx_h4 GRPEL2 8.16 6.090 0 1.59 0.83 3.26 25978 3oojO7BevD_o66E.6k CHMP2B 8.26 6 0 0 1.45 0.813.26 60436 QuR4kOirriolOeeD3o TGIF2 7.84 7.79 0 0 3.92 0.98 3.24 561656.PHwKxYKClK5Lp0ZU TDRD1 8.35 4.2 0 0.01 −1.46 0.19 3.23 50933gqTquScgS7K9XQwVc PCBP1 7.88 10.05 0 0 6.49 1 3.23 7295ckjYiQh5.0oJfoZ5K4 TXN 7.93 12.34 0 0 8.61 1 3.22 0bo8jJx7CXR5.LpO6o9.33 −5.51 0 0 0.7 0.67 0.31 ZkXTfT9DJ9noF6JcKo 9.53 −5.13 0 0 0.1 0.530.31 55173 NsgkrU7f_6.XkTf6LI MRPS10 8.08 4.36 0 0.01 −1.18 0.23 3.2155257 QpZVLnjojlH9u4eYE8 C20orf20 8.82 3.77 0 0.01 −2.23 0.1 3.21 1058xp6k.U0zIXeV9Isl0U CENPA 7.8 16.86 0 0 11.8 1 3.21 3oREUSoLRwrWb.IZ6o9.34 −5.25 0 0 0.29 0.57 0.31 6009 WpIADoapJ9EKQt9Odo RHEB 8.76 5.33 0 00.41 0.6 3.19 91612 6lTzJd4PtX1_L_cOfU CHURC1 8.57 −7.98 0 0 4.15 0.980.31 11007 ciBcmfCid5emepgg6o CCDC85B 9.29 −5.1 0 0 0.05 0.51 0.31cXUEsjvSXVwJKIIoKo 9.54 −5.02 0 0 −0.08 0.48 0.31 7019HlBzpe6NA1JeeXn.zo TFAM 8.3 6.82 0 0 2.64 0.93 3.17 6UR0b1KSAiOBzqQCqo9.25 −5.78 0 0 1.12 0.75 0.32 chEVEeDbm0BHqQJdKo 9.31 −5.75 0 0 1.080.75 0.32 29883 iLt7S.cPpO7Ked7h4I CNOT7 7.74 11.05 0 0 7.46 1 3.17 1480glJ9W1GHvtfHlQoKo ADRA1A 9.42 −5.59 0 0 0.84 0.7 0.32 286451E6LRbrU.q4QUuH6gkQ YIPF6 8.16 4.01 0 0.01 −1.81 0.14 3.16 130355cdeeAghJHeAknoNlLg LOC130355 8.23 10.93 0 0 7.36 1 3.16N0d3JT7.0cCkuCLf6o 9.6 −5.25 0 0 0.29 0.57 0.32 54815 NvUPidSV6.1xU5LyocGATAD2A 8.25 2.96 0.01 0.04 −3.68 0.02 3.14 81853 BVxIrriTsE4nz4hTTITMEM14B 8.2 5.03 0 0 −0.07 0.48 3.14 3840 E6dPsoDXuX1X_JELvk KPNA4 7.5917 0 0 11.88 1 3.14 90007 ZgWnZRXeVrCp5UICTw MIDN 7.54 8.97 0 0 5.33 13.13 6391 9q4J.q_UeXur_enwKE SDHC 7.63 11.47 0 0 7.86 1 3.13 9167fSofivk._JOq5KJf3o COX7A2L 8.12 11.88 0 0 8.22 1 3.13 14526seQeUgfrPsnnlZ4ck CSNK1A1 8.22 3.9 0 0.01 −2 0.12 3.12uAAYeVNWrX9Xjq_qS8 7.91 3.47 0.01 0.02 −2.77 0.06 3.11 653226B4RV5U.3t.DwUK7yu8 hCG_1781062 8.56 4.51 0 0.01 −0.93 0.28 3.11 51643NovrfJZ5KJX3.e6PTQ TMBIM4 8.06 8.77 0 0 5.1 0.99 3.11 uejXokAOoAJhSEkeao9.35 −6.38 0 0 2.02 0.88 0.32 EVKlYgCJ9QBTt7_qZo 9.22 −5.77 0 0 1.110.75 0.32 79877 Nu3z03e73y5Il6Vnvo DCAKD 7.85 7.21 0 0 3.17 0.96 3.11HfVQt3Oe8kVSTRQEqo 9.46 −5.52 0 0 0.71 0.67 0.32 10146l693.PjqTkurvH6A6U G3BP1 8.89 3.58 0 0.02 −2.57 0.07 3.1ENIWkPTaUTggSUvsKo 9.57 −4.69 0 0 −0.64 0.35 0.32 BU4NKGSV0UlzUYNKEY 8.6−7.21 0 0 3.17 0.96 0.32 6902 rjjjVI_UmSvoJZM.o0 TBCA 8.22 8.15 0 0 4.380.99 3.09 808 iSUInirCpKym4p7oT8 CALM3 8.74 2.85 0.02 0.04 −3.88 0.023.09 55529 9oNJ3ZHlTf5L.gAgPk TMEM55A 8.08 8.39 0 0 4.66 0.99 3.08 55233ulAekCfwvTST3O69Ik MOBKL1B 7.84 6.43 0 0 2.09 0.89 3.08 83990NqPEruJRLl6VPfi.4w BRIP1 8.79 3.11 0.01 0.03 −3.41 0.03 3.08 5558lbVIueo8a_4lHuXpf8 PRIM2 9.99 2.42 0.03 0.08 −4.62 0.01 3.07iUDOnyF_kn.iNICgio 9.32 −5.58 0 0 0.81 0.69 0.33 513880SKUYTAD0tX_19VuXU NIP7 8.03 11.14 0 0 7.55 1 3.06 cegpOQpAFOngKL0Sio9.37 −5.37 0 0 0.48 0.62 0.33 64083 HqCKfuFLFDfi.f.e1E GOLPH3 8.15 4.740 0 −0.55 0.37 3.05 6SV301Pr3l.uj0lL6o 9.67 −5.72 0 0 1.03 0.74 0.33rhN6IdevSoAS5qeE80 8.16 7.09 0 0 3.01 0.95 3.05 55322 3eF5TAxUCMwHt9RZVUC5orf22 8.79 3.86 0 0.01 −2.07 0.11 3.05 8749 rV6EyF1I_wPUv69VKo ADAM189.51 −5.49 0 0 0.68 0.66 0.33 4342 W5TR3ekDhxQkpls9qo MOS 9.29 −5.78 0 01.13 0.76 0.33 55153 3TT_J5fTHr9dJfX0l4 SDAD1 8.32 4.89 0 0 −0.3 0.433.03 253558 6dwbogOJ9OeKy6_XyI LYCAT 7.74 10.27 0 0 6.71 1 3.03 1054fb9UtVPIqfiF_xeBBU CEBPG 8.18 3.99 0 0.01 −1.83 0.14 3.03 5870x1XT6BAF8B6iBfLVd0 RAB6A 8.49 3.06 0.01 0.03 −3.49 0.03 3.02 56951xJ6CCltTXt36mhLsf0 C5orf15 8.35 7.53 0 0 3.6 0.97 3.01 202134lhQJKEPn41Si.CFJao FAM153B 9.56 −5.15 0 0 0.14 0.53 0.33 550133hfnCnAg1eASmbT3d4 CCDC109B 7.82 13.48 0 0 9.52 1 3.01cB8oElZ6CI5EqSJOqI 9.11 −5.93 0 0 1.36 0.8 0.33 2683 i6X_oCNIikiukShLAoB4GALT1 8.04 5.23 0 0 0.26 0.56 3.01 fgq.Uoebt514ne.ws4 8.54 3.78 0 0.01−2.21 0.1 3.01 10949 3pdOgNX9WN.skU3HpI HNRNPA0 8.01 7.34 0 0 3.34 0.973.01 BKUuOiMrR7ukea6Aio 9.4 −5.22 0 0 0.25 0.56 0.33 1633HXl0t5.dx7ejw8pJec DCK 7.89 16.27 0 0 11.44 1 2.99 K5.h.pTugiI4pJH1Ko9.53 −4.6 0 0 −0.78 0.31 0.33 rnqAkAIk7TrIgR5JKo 9.28 −5.17 0 0 0.150.54 0.33 3304 Tiuh76h0KH_ee.1ztM HSPA1B 8.04 4.19 0 0.01 −1.49 0.182.98 9Qk7tDNXnL16L3ORKo 9.32 −5.2 0 0 0.21 0.55 0.34 3148ukAuCSgIKlekpQSnQI HMGB2 7.74 13.44 0 0 9.49 1 2.98 81671Tp55MecDpF3qPpcXqg TMEM49 8.22 11.06 0 0 7.47 1 2.97 78994ilU3vrTU14KhKAXVKQ PRR14 7.76 8.56 0 0 4.86 0.99 2.96 1163lgUgXRN_e9aZUcVCAU CKS1B 7.81 11.21 0 0 7.61 1 2.96 8545ZS9NP658t.sKnd7r_E CGGBP1 7.96 15.35 0 0 10.85 1 2.95 3QAgAvknv_E94OfcI8.32 4.99 0 0 −0.14 0.47 2.95 400629 0veju_l4OnvuefuE6o FLJ35767 9.42−5.22 0 0 0.24 0.56 0.34 114569 fengk1X6LlOzC_pzyI MAL2 8.62 7.24 0 03.21 0.96 2.94 1539 9IJEft2d75Xp6L0uE4 CYLC2 8.61 3.02 0.01 0.03 −3.560.03 2.93 54206 Nnunn0fI5LiETL671g ERRFI1 8.22 3.84 0 0.01 −2.1 0.112.93 7529 feXBv597jrzPlyQkRU YWHAB 8.05 5.31 0 0 0.38 0.59 2.93 10294uAA6n_REOr_ieHqBDo DNAJA2 8.02 8 0 0 4.18 0.98 2.92 Wu.75CAC_Se.74T3g47.9 5.5 0 0 0.68 0.66 2.92 8905 fueRH8SSfX9.U6R5cs AP1S2 7.76 10.35 0 06.79 1 2.92 55858 xFvuS6rcU5D.f0keFU TMEM165 7.65 16.68 0 0 11.69 1 2.9251444 rcYEbgoAknW1EGWfao RNF138 9.52 −5.37 0 0 0.48 0.62 0.34 90488cqz_kQ4owHzuFR_Dp4 C12orf23 8.19 4.87 0 0 −0.33 0.42 2.92WkC6ASkrQbbrTe6r5o 9.2 −5.79 0 0 1.13 0.76 0.34 255919T1zl9FIMH6i65SAci0 TMEM188 8.36 8.34 0 0 4.6 0.99 2.91 6319Nyg7UU4H4xtbu1SOe0 SCD 8.12 3.88 0 0.01 −2.02 0.12 2.91Tnzt7MoO0S5COeclSk 8.61 3.97 0 0.01 −1.87 0.13 2.91 64968EDF16j7ictPSXuwU7o MRPS6 8.27 5.57 0 0 0.79 0.69 2.91 23367WigB_03p.miCvUXxnY LARP1 7.98 4.95 0 0 −0.2 0.45 2.9 3017Wc8GcY5eBcULedeVQI HIST1H2BD 7.71 11.31 0 0 7.7 1 2.9 103909iUjWS66IvcO_Hv5KU CEPT1 7.97 11.67 0 0 8.03 1 2.9 60559H5OvxXeLzv33LiTl54 SPCS3 7.97 7.29 0 0 3.28 0.96 2.9 9112Qn_78f.p6JojiqUVbk MTA1 7.7 8.69 0 0 5.02 0.99 2.89 54830oJfvfK.oEt63Xu.Tv0 NUP62CL 7.93 7.1 0 0 3.03 0.95 2.89EqeASNXjlSPVEB4QKo 9.38 −4.91 0 0 −0.27 0.43 0.35 6046Kleqv0tN1U.rVeh7f4 BRD2 8.24 3.17 0.01 0.03 −3.29 0.04 2.88 51478Eyeruuk5k7LVJx0go4 HSD17B7 8.76 3.14 0.01 0.03 −3.34 0.03 2.88cfA.qS5JzUx3ft7wqo 9.29 −5.76 0 0 1.09 0.75 0.35 9hIC13n19KV_fUfVao 9.39−5.86 0 0 1.24 0.78 0.35 84932 flAfl.n0dNOSX3q_vk RAB2B 7.82 9.14 0 05.52 1 2.87 650832 EAQeVNWrX9Xjq_6S8U LOC650832 8.04 3.17 0.01 0.03 −3.30.04 2.87 22822 9BLd1lWRSNCy.oTRXE PHLDA1 7.79 12.33 0 0 8.6 1 2.8710552 WCeLiXWU1JOEB7pYWQ ARPC1A 8.03 7.29 0 0 3.27 0.96 2.86 9278QjqxHglXnUSLI_ROio ZBTB22 9.16 −5.58 0 0 0.81 0.69 0.35 647000H1.UHcXV0didf1XjSI LOC647000 7.94 7.25 0 0 3.23 0.96 2.86 27430ul15.zJL86okfgIm7s MAT2B 8.03 5.68 0 0 0.98 0.73 2.85 55143o7h_frpdPU7uXuXqk4 CDCA8 7.76 5.76 0 0 1.09 0.75 2.85 3183ZTw9M_VZly1T.R9f4Y HNRNPC 8.11 6.69 0 0 2.46 0.92 2.85 7733HJXe8Pu7dA.vegCAqo ZNF180 9.34 −5.61 0 0 0.86 0.7 0.359_sE6_JdXSYF596Hao 9.37 −5.88 0 0 1.27 0.78 0.35 BZoRmAbhB4ToiBQcao 9.42−5.37 0 0 0.48 0.62 0.35 1460 lheUFL_5Up3Gv0I1NY CSNK2B 7.76 10.76 0 07.2 1 2.84 8323 KSxf3SE.7IPT9pJ0co FZD6 8.1 6.15 0 0 1.68 0.84 2.84 6732HpJ7I3431KxVOxfz4k SRPK1 7.89 5.23 0 0 0.26 0.57 2.83 23291oVdvX6iOOl.gzkhBf4 FBXW11 8 3.83 0 0.01 −2.12 0.11 2.83u_M5UdFdhg3lZ.qe64 7.86 4 0 0.01 −1.82 0.14 2.83 27020iqfBe4fwwnoEtR4OrM NPTN 8.2 5.48 0 0 0.66 0.66 2.82 23480xnG7V6T.K7a_pLTo0o SEC61G 7.86 7.08 0 0 3 0.95 2.82 55326uOW2O5Of87.0gCru.o AGPAT5 8.1 4.49 0 0.01 −0.97 0.28 2.819uAVI.JP.rXL.UiNKo 9.48 −4.7 0 0 −0.62 0.35 0.36 803063qL.LbKXzjDxVmuu7I MED28 7.92 9.6 0 0 6.02 1 2.81 81542WQ.ew7Vff3Kd757uDU TXNDC1 8.12 5.7 0 0 0.99 0.73 2.81 9978cf5Mg7QnBSm1nH0gi4 RBX1 7.66 13.68 0 0 9.67 1 2.8 6436lOp5eiVeu1eiJuiIKo SFTPA2B 9.26 −5.35 0 0 0.45 0.61 0.36 2069iTe5WP8s7kqqY3qDS0 EREG 7.56 18.46 0 0 12.7 1 2.8 389792NmX.d31AMC1CHoi5qo IER5L 9.25 −5.21 0 0 0.22 0.56 0.36 388951ZrncpKgB4EAKSA49Ko TSPYL6 9.14 −5.41 0 0 0.55 0.64 0.36 3020fmSc2uf5KKQuKXN6_k H3F3A 7.71 9.83 0 0 6.26 1 2.8 o3u4r4MI17t1Iit46o9.27 −5.47 0 0 0.65 0.66 0.36 WrgWV_HwGUETcAqpio 9.08 −5.61 0 0 0.86 0.70.36 6613 Kf.7Gye8TsqQ3t.Cyo SUMO2 9.7 6.33 0 0 1.94 0.87 2.79 23568x99e0A3dcUI671HtSU ARL2BP 7.91 4.24 0 0.01 −1.4 0.2 2.79 8799fXfXV87cXRQXZ00.pU PEX11B 8.28 7.43 0 0 3.47 0.97 2.79 6421BI_6Dq7CEPrKq4C6v4 SFPQ 8.42 4.18 0 0.01 −1.5 0.18 2.79 10276ZqbssL7IKdiqG6Hz_U NET1 8.25 4.36 0 0.01 −1.2 0.23 2.78cUr8U3R1SwxUnXNwJU 7.89 5.58 0 0 0.81 0.69 2.78 827 iUh10h.3dL6jn0dnqoCAPN6 9.18 −5.86 0 0 1.25 0.78 0.36 51765 09tew3v3K4JMdS7.KoRP6-213H19.1 9.51 −4.78 0 0 −0.48 0.38 0.36 3576 3Vy3nJSjUQtfvUe5fo IL87.47 14.82 0 0 10.49 1 2.77 ZutQKQL2oQnQwfLfv4 8.24 5.47 0 0 0.64 0.652.77 6747 xlHI6S5ezI6oAD5RT0 SSR3 7.69 16.47 0 0 11.57 1 2.77N7e01L5L_G7eiOoS6o 9.08 −5.18 0 0 0.19 0.55 0.36 114882NXkuwsSRHtA9.18K5E OSBPL8 7.85 7.23 0 0 3.2 0.96 2.76 29978EuSXgo0uyw5SgLn.xc UBQLN2 7.87 9.1 0 0 5.48 1 2.76 161742BvwUf55wj.ltU9U..U SPRED1 8.01 5.48 0 0 0.65 0.66 2.76WUZmAPaUq92d_2bedA 7.64 15.91 0 0 11.22 1 2.76 25907 EgX.UL43NS4bpeupv0TMEM158 8.2 3.35 0.01 0.02 −2.98 0.05 2.76 6752 TXbMJ9CXRAX3Jd5X6o SSTR29.43 −5.76 0 0 1.09 0.75 0.36 3NDg8gVCdQkNdcg.Ko 9.11 −5.92 0 0 1.330.79 0.36 Tse_fo5pEuvrDoMCjk 8.48 2.48 0.03 0.07 −4.51 0.01 2.75No9r9q9Lg0qS7.UP6o 9.19 −5.26 0 0 0.31 0.58 0.36 5270 Qt_chCvnvuS717Rx60SERPINE2 7.98 7.96 0 0 4.13 0.98 2.75 11112 E6HW0QzrKM1dFB1YR0 HIBADH8.06 5.3 0 0 0.38 0.59 2.75 440275 6OjTeJdKK_KeS4nuHk EIF2AK4 8.33 3.260.01 0.03 −3.13 0.04 2.75 83641 Eqlesp1.IKFP3vXInw FAM107B 8.18 4.43 00.01 −1.07 0.25 2.74 440026 rRCCEJN7rmikJKcHKI TMEM41B 7.83 15.02 0 010.63 1 2.74 51112 QBBnlu7edxepCdCh1c TTC15 8.25 −6.38 0 0 2.02 0.880.36 56203 fVyA8gDQn_pSua6dOU LMOD3 8.46 3.78 0 0.01 −2.2 0.1 2.74BV69MIpw5ItEtJU16o 9.23 −5.24 0 0 0.28 0.57 0.36 QL0UFXqNL6nEu.dgqo 9.1−5.95 0 0 1.38 0.8 0.37 10413 Nro.zXZCTvvMIPuruU YAP1 8.31 5.01 0 0 −0.10.48 2.74 9525 9q37X0X.C9KgS.teFE VPS4B 7.75 8.8 0 0 5.14 0.99 2.74Kr6LkumY3SeHklXn1Q 9.16 2.68 0.02 0.05 −4.17 0.02 2.74 11165c3giKUEl9V5fo94LvU NUDT3 8.34 3.97 0 0.01 −1.87 0.13 2.74 9554BMozoilXp9OIECkpUo SEC22B 7.99 16.2 0 0 11.4 1 2.74 3460KCF62234f6QOJaJV_o IFNGR2 8.27 9.91 0 0 6.35 1 2.73 7334cavkF_3fkvwrDoz7JU UBE2N 8.01 11.32 0 0 7.72 1 2.73 64783Qp0RJ8Isnt3QG5nRL4 RBM15 8 4.87 0 0 −0.33 0.42 2.73 Kf8ECp.VU9oJL6QKpo9.02 −5.59 0 0 0.83 0.7 0.37 140609 9phS.dEg_4JeClCKC0 NEK7 7.6 13.94 00 9.86 1 2.73 79192 ESV1bWXjwq33.H.mqo IRX1 9.16 −6 0 0 1.45 0.81 0.3751727 Nyg4vfNy75KUkDEius CMPK1 8.18 9.02 0 0 5.39 1 2.71 278urSS3eNbkqzw7tKni4 AMY1C 7.97 7.23 0 0 3.2 0.96 2.71 46739HL.3lJzvg5ED3tGTs NAP1L1 7.65 12.49 0 0 8.73 1 2.71 378xVcT4delxNJQHwX66o ARF4 8.42 7.25 0 0 3.22 0.96 2.71 o_j5N4OSB.rbUsVI788.23 −7.97 0 0 4.14 0.98 0.37 EotPMuzV4i3i1Liv6o 9.32 −5.07 0 0 0 0.50.37 Te_ciWQc7Kyix76fao 9.29 −5.55 0 0 0.77 0.68 0.37 3682QgfoiTSgpUngNIg3nY ITGAE 7.73 17.67 0 0 12.27 1 2.7 EHOtPME0r_IAH03K6o9.24 −5.4 0 0 0.54 0.63 0.37 79027 EIl0v7koRYToEqHR6o ZNF655 9.18 −5.820 0 1.19 0.77 0.37 91746 TPXO9LJuvjnPvyX1XU YTHDC1 8.28 7.42 0 0 3.440.97 2.7 HqDQ14t.5FKS0.qJ6o 9.06 −5.48 0 0 0.66 0.66 0.37 5037os7R3rV.AiQ16CCSio PEBP1 9.13 −5.43 0 0 0.57 0.64 0.37 7358EVK3TX0oP_S9DiCKiE UGDH 8.1 5.98 0 0 1.43 0.81 2.69 688KboBEXE4AkgNr57.n0 KLF5 7.92 6.86 0 0 2.7 0.94 2.69 7323067qL7Tinu_C4fNzuo UBE2D3 8.86 2.91 0.01 0.04 −3.76 0.02 2.68 64332N_flnpOXig7P6f48RE NFKBIZ 8.21 7.22 0 0 3.18 0.96 2.68 6428TVHvFPvfNU6gkvrxGM SFRS3 8.01 6.87 0 0 2.71 0.94 2.68 5111umjOoR8Axx_nVCNijg PCNA 7.83 8.79 0 0 5.12 0.99 2.68 349334HE.BExMApLAhA4giqo FOXD4L4 9.12 −5.89 0 0 1.29 0.78 0.37 6670KkuP.NQ379QAU7dUqU SP3 8.24 5.14 0 0 0.12 0.53 2.68 66363sl5BPaW6.E4vxV0NU SNRPF 7.63 14.52 0 0 10.29 1 2.68 25798N1X_r0.nv_X4oJhjlU BRI3 7.58 12.41 0 0 8.67 1 2.68 55793xX16r_gMAfelqRrp0c FAM63A 8.21 3.83 0 0.01 −2.12 0.11 2.68 91272iykwoB2.kp3e1Knn14 FAM44B 8.2 4.8 0 0 −0.44 0.39 2.67 91413lQvejS2lalK8LB8kc PDCD5 7.73 8.08 0 0 4.29 0.99 2.67 818489l.eEv7tglUud5egF4 SPRY4 8.31 −8.19 0 0 4.42 0.99 0.37 7851WcT.1XXqv5qhKhIHEo MALL 7.6 12.22 0 0 8.5 1 2.67 3837 Z0g_kkQIAZXdeH7PukKPNB1 8.2 3.65 0 0.02 −2.43 0.08 2.67 1607 WebrTShiQt3lDkD46o DGKB 9.07−5.56 0 0 0.79 0.69 0.38 1716 fSVd01eiR3lnQiev7w DGUOK 7.84 7.92 0 04.08 0.98 2.66 9477 rJd5BC0rrrTv1fcv_k MED20 7.61 17.37 0 0 12.1 1 2.66154043 05P_F70u3t9SRruxH0 CNKSR3 7.53 11.79 0 0 8.14 1 2.66 2504oiSuCU0CDquFG4UH7k FTHL12 9.3 2.34 0.04 0.08 −4.76 0.01 2.66 25801xvrrv4q_nIDgJej.uU GCA 8.48 11.18 0 0 7.59 1 2.66 80143lS60Hq9HTQdPVtUvx0 SIKE 8.38 3.15 0.01 0.03 −3.33 0.03 2.65WeKEgtu.QstKLjqiuo 8.96 −5.45 0 0 0.6 0.65 0.38 1479 QkaCHzgZfvlS9VL3pICSTF3 7.82 10.69 0 0 7.13 1 2.65 oXqToNe6TUQBxfQdTI 7.82 11.28 0 0 7.681 2.65 200845 KpLihSCgv_5.pIddTs KCTD6 7.79 13.39 0 0 9.45 1 2.65 2836516S7tKQ3of5XQCJLr14 C15orf21 7.69 16.9 0 0 11.82 1 2.65 58516NVfUXd.l7KOx7Oy05E FAM60A 7.8 8.08 0 0 4.29 0.99 2.65 8763TvI.5C3EDid_QSB0SU CD164 8.26 8.63 0 0 4.94 0.99 2.65 Q3Sfd1WEXo4dd_nF6o9.22 −5.95 0 0 1.39 0.8 0.38 441394 E0g6dIN4ri3R3tlSno SUGT1P 8.85 2.720.02 0.05 −4.1 0.02 2.65 6780 rBUoS.S45A_7ld69J4 STAU1 7.64 18.49 0 012.72 1 2.65 oVIueo8S_4lHuXrf38 9.45 2.3 0.04 0.09 −4.82 0.01 2.65 37776MeKXoSuC4UiJAKQKo KCNK3 9.13 −5.26 0 0 0.32 0.58 0.38 659799XicfvZfe5tFCw3r00 PHACTR4 7.83 9.09 0 0 5.46 1 2.64 cCu0fl2v1UQKuIgoqo8.92 −6.09 0 0 1.59 0.83 0.38 ZW.HUer7gj0SCOEoKo 9.14 −5.98 0 0 1.430.81 0.38 9CLKLvRLl_6K0viIuo 9.23 −4.64 0 0 −0.71 0.33 0.38 51012fmuqCBCTDrKqKfpeAc SLMO2 7.9 8.66 0 0 4.98 0.99 2.64 3075uSUg6gOcPSddSklQ6o CFH 9.09 −5.47 0 0 0.64 0.66 0.38 65177164Va9Z4jSCkEneL1Ko LOC651771 9.17 −5.1 0 0 0.05 0.51 0.38 933800k_6fdLp_Ek316_zuk TMEM32 7.99 8.98 0 0 5.34 1 2.63 51301rf_uTx_tD0q_KIe_qo GCNT4 8.91 −5.5 0 0 0.69 0.67 0.38 8533NFN_lLhC72ipJIihQk COPS3 7.59 8.63 0 0 4.94 0.99 2.63 lkn6jt4IOAJcIhClao9.22 −5.37 0 0 0.48 0.62 0.38 cm4lFmVpfyDn8P93SI 8.83 2.87 0.02 0.04−3.83 0.02 2.63 9588 i6dUKK7JK7iQzy5TuU PRDX6 7.72 7.28 0 0 3.26 0.962.63 5962 KevBfguHvsU6_5E59I RDX 7.66 10.16 0 0 6.6 1 2.63 7132lioZzl05W.6u10UkKc TNFRSF1A 7.73 6.93 0 0 2.8 0.94 2.63 26097QOmSEjVgFDj4JeVNdU C1orf77 7.95 5.14 0 0 0.11 0.53 2.63 10434udS5Rqj7hX_vVeO.r0 LYPLA1 7.97 14.22 0 0 10.07 1 2.62 558119Dul314ESX5p3eARKo ADCY10 9.24 −4.9 0 0 −0.28 0.43 0.38 54806fi6R4weuCXElNZUAt4 AHI1 7.96 9.75 0 0 6.18 1 2.62 55795Hm4Kedp0f9cLuvXgp4 PCID2 7.78 5.78 0 0 1.12 0.75 2.62 1761uljpr0fosEp89R.U6o DMRT1 9.34 −4.75 0 0 −0.53 0.37 0.38Wpe5wM16M_.MrSAe6o 9.04 −5.49 0 0 0.68 0.66 0.38 10728Hd8k6KGCAnsT75_It4 PTGES3 8.06 5.47 0 0 0.64 0.66 2.61 10252xl9s.uCh0lF9ffRVOc SPRY1 7.71 16.92 0 0 11.84 1 2.61 84436rXqdCS195fJdcLJ4hw ZNF528 8.67 2.91 0.01 0.04 −3.76 0.02 2.61 6184iSPq6y6ivuTopS4CeE RPN1 7.94 4.34 0 0.01 −1.22 0.23 2.61 55069BPSA_tQw5G5.lerElI C7orf42 7.73 14.42 0 0 10.21 1 2.6 865Efl8JxSPn.lFPpTHu4 CBFB 8.17 6.77 0 0 2.57 0.93 2.6 7288HUlHA4EotnHi28UG6o TULP2 9.21 −4.88 0 0 −0.31 0.42 0.383lEvo9eFRIBjiMfp6o 9.08 −6.73 0 0 2.52 0.93 0.38 3187 ipuBoOoq_3JO1LOLroHNRPH1 7.76 10.91 0 0 7.34 1 2.6 11157 oTSxEgiGjuCEUIiQZ8 LSM6 8.1711.96 0 0 8.28 1 2.6 8428 6md23hP7_g25R563mU STK24 8.45 3.31 0.01 0.02−3.05 0.05 2.59 83698 ZUyU31dRF4_dB5VIKo CALN1 9.19 −5.3 0 0 0.37 0.590.39 10621 QlO4CoghATUYFKC6tc POLR3F 7.89 10.04 0 0 6.48 1 2.59 1964BKTGmJ9SJOcA0OAeMQ EIF1AX 7.71 10.49 0 0 6.93 1 2.59 517263F3V.qj8O3rnll4v0I DNAJB11 7.93 7.84 0 0 3.98 0.98 2.59 55954W1_p0JzXVF0l3QMnqE ZMAT5 8.87 2.29 0.04 0.09 −4.84 0.01 2.599mu.guECnnuEACSoCo 9.06 −5.59 0 0 0.84 0.7 0.39 BRuDqROl1RJCjnbw6o 9.08−4.97 0 0 −0.17 0.46 0.39 54477 Qf3a0j5DtJLx5RHXtI PLEKHA5 8.28 5.31 0 00.39 0.6 2.58 374969 rH0evXVN4PpROfngiE CCDC23 7.61 15.7 0 0 11.08 12.58 umSgQB1IKiFoIpAxqo 9.02 −6.05 0 0 1.53 0.82 0.39 r4ASIJ7xEzKirMQoCs7.75 8.42 0 0 4.69 0.99 2.58 127933 Ev0skz636T9_ke6954 UHMK1 7.83 4.98 00 −0.15 0.46 2.58 23314 HkuvcLg3upP8l7rflI SATB2 7.72 10.96 0 0 7.39 12.58 B0GDC3U_1LTpPR3l6o 9.24 −4.92 0 0 −0.24 0.44 0.39 5354KQFLMQjCfUp5Mgooio PLP1 8.86 −6.87 0 0 2.71 0.94 0.39 7329l9dneo5KTn3RbkieR8 UBE2I 7.68 7.21 0 0 3.17 0.96 2.57 6659BE4SkcobeX.wpL1vCo SOX4 8.41 8.06 0 0 4.26 0.99 2.57 131566QRf5Xp3k_0XIiQitzI DCBLD2 7.84 5.61 0 0 0.86 0.7 2.57 6541EdV._eEEe7E_FH1xTE SLC7A1 8.53 2.77 0.02 0.05 −4.01 0.02 2.57 4247foB4JJCLleDuO93V6o MGAT2 9.5 −4.61 0 0 −0.77 0.32 0.39WSEgO1eV0aL8TXqy6o 9.01 −4.71 0 0 −0.6 0.36 0.39 WdS75zuQjXd_if.5Mk 8.255.56 0 0 0.79 0.69 2.57 54534 uqR7Qfq.CEooT5C9EU MRPL50 7.97 7.43 0 03.46 0.97 2.57 lS303h3r11910gigYU 7.62 14.82 0 0 10.5 1 2.57 51124ElRCJLXAQ0Q8R7HFQg IER3IP1 7.88 9.22 0 0 5.61 1 2.56 10635lV.9_MUdNRu9ePtRP0 RAD51AP1 7.82 15.28 0 0 10.8 1 2.56 346007x7ukPqP5KN4KYAuUKo EGFL11 8.99 −5.04 0 0 −0.05 0.49 0.39uxNAlzoyMKggPygOqo 9.01 −5.23 0 0 0.27 0.57 0.39 1112 xKn6Ovgd7Hl_7kfSVYFOXN3 7.68 12.03 0 0 8.35 1 2.56 51201 WoSj2PCz1d_0B6Ccqg ZDHHC2 7.982.82 0.02 0.04 −3.92 0.02 2.56 93081 xR6PiCkDT1OkuAoa2E C13orf27 7.918.92 0 0 5.27 0.99 2.56 6715 0TGiwnneXu4unXqVwE SRD5A1 7.58 17.22 0 012.01 1 2.56 iV_kEf0YN.RpXU_mRM 8.24 −8.11 0 0 4.32 0.99 0.39 7295obSHUklCOuCSNiJCHk TXN 7.75 11.94 0 0 8.27 1 2.55 284613EV3.U.dXU0UXldE16o CYB561D1 9.32 −4.78 0 0 −0.48 0.38 0.3930kJd76O10lXs7zoio 9.05 −5.88 0 0 1.28 0.78 0.39 29883igaMoUQTSko3j0_dEo CNOT7 8.13 11.03 0 0 7.45 1 2.55 26986Z3lXXQiQCQO_rgae.U PABPC1 8.21 5.36 0 0 0.46 0.61 2.55 7295lTa18SWdtIdSSUI64I TXN 7.87 10.36 0 0 6.8 1 2.55 51014rrSTqTOwDtf96_Xdzk TMED7 8.22 5.8 0 0 1.16 0.76 2.55 83543cro4LO7ubuTqLuboeo C9orf58 9.81 −9.73 0 0 6.15 1 0.39 NYhQiQ484OkLpCAaro8.77 −6.48 0 0 2.16 0.9 0.39 81603 fiqeVovq1_Xo.4RJB8 TRIM8 7.86 4.49 00.01 −0.96 0.28 2.54 3892 uRZZVcW6TdecWaXRao KRT86 9.18 −4.73 0 0 −0.570.36 0.39 NuI56tTXBLiz1BI1qo 9.06 −5.94 0 0 1.37 0.8 0.39 647319fF0qErN7u28RAEvcqo VEZF1L1 9.13 −5.57 0 0 0.8 0.69 0.39EXgQxRRVTOVcQQAIqo 8.89 −5.59 0 0 0.83 0.7 0.39 ESCov8IoD60ebtN2Ko 9.01−4.83 0 0 −0.4 0.4 0.39 flNOuHtOvcSA5XU7tU 8.02 4.25 0 0.01 −1.39 0.22.54 TikHp8jRoNUCKRKH6o 9.11 −5 0 0 −0.12 0.47 0.39 6597fW1HXXHs.z6ErSHZao SMARCA4 9.25 −5.32 0 0 0.4 0.6 0.39 f3o7s_J67V76qCio9.05 −4.9 0 0 −0.28 0.43 0.4 26985 BSnouS6ZDfJ3cSbY30 AP3M1 10.23 2.650.02 0.06 −4.21 0.01 2.53 644316 uIjqv_dLQUlSnouS64 FLJ43315 9.62 2.880.01 0.04 −3.81 0.02 2.53 26034 Zufk46g7h.yR5Ou.qo PIP3-E 8.99 −5.94 0 01.37 0.8 0.4 KUM97_MxFKKBOKKH_o 9.14 −4.61 0 0 −0.76 0.32 0.4lz3dA9fim4lFmVJe10 8.72 2.7 0.02 0.05 −4.13 0.02 2.52 6662ruKinF6Ko01R4SF8N8 SOX9 8.12 5.76 0 0 1.09 0.75 2.52 64081QovYhSXqQRJiB_3c8A PBLD 9.01 2.6 0.02 0.06 −4.3 0.01 2.52 50808WunPH_9_tfRKl51NUU AK3 7.89 9.85 0 0 6.28 1 2.52 80829rl77DuShX3X9OoiErI ZFP91 7.92 4.52 0 0.01 −0.92 0.29 2.51 8915Hl3.4x6KBH46LuJRcI BCL10 7.81 11.21 0 0 7.61 1 2.51 79752lTulCXJNOiUgLMl_e0 ZFAND1 8.27 12.14 0 0 8.44 1 2.51 51762lgiE9f.X7xNQqqRKro RAB8B 9.13 −5.73 0 0 1.05 0.74 0.4 54407BvIpQQ9yzp_kCLnEU SLC38A2 8.4 5.02 0 0 −0.08 0.48 2.5106lnSCCXUd1JBLt9Sg 8.45 −6.19 0 0 1.74 0.85 0.4 221035f90lDU9EJ_k_E7nnL8 REEP3 7.54 11.32 0 0 7.71 1 2.51 105340jAjDVneDlSnld1QnY SSSCA1 8.2 −8.59 0 0 4.89 0.99 0.4 ZEF7Ln6t4faSV2rEt48.16 −8.63 0 0 4.94 0.99 0.4 4218 6nhZEkt6fj.SW00_r0 RAB8A 7.57 12.83 00 9.01 1 2.51 7555 fqCL4tIUsJW16vX4E4 CNBP 7.96 5.02 0 0 −0.07 0.48 2.583875 uMBHih1AKqkKKCKpKo BCDO2 8.95 −5.51 0 0 0.71 0.67 0.4Qn52erfo7avYUfpY6g 8.13 2.66 0.02 0.06 −4.21 0.01 2.5 56616Z4.LH71d76jlL7pKqI DIABLO 9.01 −5.71 0 0 1.02 0.73 0.4 4149rnkulnV6lsoDiYwY4Q MAX 7.74 8.34 0 0 4.6 0.99 2.5 10914KXojSHvn9k47Oy7dOE PAPOLA 8.18 3.31 0.01 0.02 −3.05 0.05 2.5 54915Nov4vgk4A65U5eGdSY YTHDF1 8.28 2.86 0.02 0.04 −3.84 0.02 2.49 1432790Piynigiiq_t_e3Suk HECTD2 7.94 5.47 0 0 0.64 0.66 2.49 6235BmAPaUq92d_27e9AWk RPS29 8.01 8.61 0 0 4.92 0.99 2.49 9538iRwF4H.Qdb666ikmpI EI24 7.76 5.08 0 0 0.01 0.5 2.49 284930rOA0CAAwOIOUgE6ouo LOC284930 8.95 −5.61 0 0 0.86 0.7 0.4BUJ07kCI3kHSBJ0Qqo 8.99 −5.74 0 0 1.05 0.74 0.4 26130 6DE0YpSe7j94hcjiLUGAPVD1 7.7 9.48 0 0 5.89 1 2.48 8886 lofUF_Hnidenyffq9c DDX18 7.59 15.390 0 10.88 1 2.48 6146 HQjRbhNYrl.dQCs.gM RPL22 8.39 3.11 0.01 0.03 −3.40.03 2.48 WaSZeoQrfSBxySMP6o 9.02 −5.44 0 0 0.6 0.65 0.4 37273nGLUT17_w1_vZWv94 JUND 10.42 2.88 0.01 0.04 −3.82 0.02 2.48 8470W5dWOuc9PtRXFIOHmo SORBS2 9.12 −4.39 0 0.01 −1.13 0.24 0.4xgoK4ArK4o7qooqKCo 9.21 −5.32 0 0 0.41 0.6 0.4 3638 QUUtJIOgnyKB_XuJnoINSIG1 7.86 9.07 0 0 5.44 1 2.48 6152 9CHkOnnnCkXECkkXCQ RPL24 7.6 11.990 0 8.31 1 2.48 29080 lN55c8r33uE7l1SS4E CCDC59 7.63 9.27 0 0 5.67 12.48 2171 0C.ggFEnjpIAHSHt5A FABP5 7.34 14.27 0 0 10.11 1 2.48 7178ihNxCNaiNmhq_5eiug TPT1 8.11 5.17 0 0 0.17 0.54 2.48 6698xHict9_dq5P4o6P6o SPRR1A 9.05 −4.39 0 0.01 −1.14 0.24 0.4 1582936kq6kuInnOg0OhAeEo FAM120AOS 7.72 6.53 0 0 2.23 0.9 2.47 284058HnVfl7oE_3rXJ7r1T4 KIAA1267 7.56 11.76 0 0 8.11 1 2.47 23603xWypO69AiCSipCoC8U CORO1C 7.83 3.65 0 0.02 −2.43 0.08 2.47TjqA8uui7tOBTtl7HY 7.99 10.77 0 0 7.2 1 2.47 6AnlNC0SlKtN0KdF6o 8.87−6.08 0 0 1.58 0.83 0.4 9698 rtyX5WJ.XxDSJV3Rfs PUM1 8.36 6.15 0 0 1.670.84 2.47 51031 ri7UigEgKDi7uG_eRk GLOD4 7.9 7.64 0 0 3.74 0.98 2.472152 r6m4FFOVJYAn.iqeH0 F3 7.73 5.34 0 0 0.44 0.61 2.47 79698oIiGCVRiURXHcQigKo ZMAT4 9.05 −5.79 0 0 1.14 0.76 0.41H1aD_l3qEQV96gT9qo 8.94 −6.44 0 0 2.11 0.89 0.41 10109ZigmnpB4KegR_cejDY ARPC2 7.99 5.51 0 0 0.71 0.67 2.46 7321Kksnsgs7CDO46uy08k UBE2D1 7.61 14.79 0 0 10.48 1 2.46 2782H9bUEHeyJ3eRXxV.UU GNB1 8.21 2.79 0.02 0.05 −3.98 0.02 2.46 5049TvooBF4ogEBRT5eHp0 PAFAH1B2 7.59 13.29 0 0 9.38 1 2.46 4403593bZUb3XBnX0QjpAilE LOC440359 8.35 6.52 0 0 2.22 0.9 2.45c8ohusrR3sTvfXSQqo 9.02 −5.89 0 0 1.29 0.78 0.41 220213rpMDt6JQX6S8ySiBHs OTUD1 8.13 6.46 0 0 2.13 0.89 2.45 5836oNQKXoEQ6x0AEyeXao PYGL 9.2 −5.66 0 0 0.95 0.72 0.41 o5yiuA3vkCeD8wryqo9.02 −5.73 0 0 1.04 0.74 0.41 140901 HAT_7qEhibior.CUpE STK35 8.05 4.140 0.01 −1.58 0.17 2.44 474338 fdeh7h.S6iOgu.SIHg SUMO1P3 7.67 15.61 0 011.03 1 2.44 23399 HmJX6jlt45XtQ7ih5c DULLARD 7.51 5.51 0 0 0.71 0.672.44 57179 KSpegZe5qitHQ9AP94 KIAA1191 7.95 4.39 0 0.01 −1.14 0.24 2.44125476 6mvSRT4Iv9cT2inld4 C18orf37 7.61 16.36 0 0 11.5 1 2.44TpCRGBESEUjERgEiqo 8.82 −5.92 0 0 1.34 0.79 0.41 H0gbXSBZKJQigN1bKo 8.83−6.45 0 0 2.11 0.89 0.41 4809 H3iJX1Xu15RTurSOx0 NHP2L1 7.99 5.38 0 00.5 0.62 2.44 5634 HeDqroXpPzelABKJSI PRPS2 7.66 13.51 0 0 9.54 1 2.44Et1LjHiy3T0inVwuqo 8.71 −6.89 0 0 2.73 0.94 0.41 64100T9jiASS6A97gGDizqo ELSPBP1 8.94 −5.68 0 0 0.97 0.72 0.41rOkKjJLcU.F8qce79c 8.17 −6.8 0 0 2.61 0.93 0.41 3066 QKBQNIEnSQVeD_Et0UHDAC2 7.82 11.53 0 0 7.9 1 2.43 57187 ElFofBQiGwIog6BDqo THOC2 8.91−6.37 0 0 2.01 0.88 0.41 5501 lGLhY85.f6XE9.Pea4 PPP1CC 8.16 3.32 0.010.02 −3.03 0.05 2.43 10890 BKn_Vf97C3fqNe7IJ4 RAB10 8.11 5.59 0 0 0.820.7 2.43 55432 ZS.1LRPrlPSh1J78Sg YOD1 7.75 6.26 0 0 1.84 0.86 2.4326154 x5Qywnkq6BCA0fneqo ABCA12 8.7 −5.76 0 0 1.09 0.75 0.416tRLgtR1K83kyslSkU 7.99 7.57 0 0 3.65 0.97 2.43 29058 iedOPUKNJejlyKHI0UC20orf30 8.19 3.78 0 0.01 −2.21 0.1 2.42 QXqIDgCRrTxJ0v6c6o 9.02 −4.95 00 −0.2 0.45 0.41 4893 Hr.Uil7.qn9UogI4B4 NRAS 8.34 3.5 0 0.02 −2.7 0.062.42 11034 x0pE0_gxKCyV5F5S4k DSTN 7.66 9.04 0 0 5.41 1 2.42oJIiyDrryIp6i_BoOo 8.95 −5.21 0 0 0.22 0.56 0.41 133383TlR9ju_9_2R8qE0NCg C5orf35 7.78 15.24 0 0 10.78 1 2.41uyIInOFPrK7U_dVyuo 8.93 −5.1 0 0 0.04 0.51 0.41 57122 xnSItd3DnXIUqH4VPINUP107 7.93 8.2 0 0 4.43 0.99 2.41 1486 TapPpO6DkB7fhx3ojk CTBS 7.4415.93 0 0 11.23 1 2.41 rhNHa3uH2uQ3X0qCWo 8.66 −6 0 0 1.45 0.81 0.42201895 EujpL.ey.6oe6yd_j4 C4orf34 8.13 8.47 0 0 4.75 0.99 2.41 10381l11UXKUbuJ517d7fPk TUBB3 7.57 7.92 0 0 4.09 0.98 2.41 6120c_d7RUp4LkukS0qVPk RPE 9.63 2.78 0.02 0.05 −4 0.02 2.41 3146x5P787D9KKDHgTeLXo HMGB1 8.56 2.96 0.01 0.04 −3.68 0.02 2.41 11177cX4LnsUuenkrPC1C.M BAZ1A 7.95 5.43 0 0 0.57 0.64 2.4 51026iq.jDdUtfLAj4iKeiQ GOLT1B 7.65 13.56 0 0 9.59 1 2.4 ECUSFSKp0fi_4ogCqo8.91 −4.86 0 0 −0.34 0.42 0.42 23016 N67a4UkKi_4bk4oC6o EXOSC7 9.13−5.02 0 0 −0.07 0.48 0.42 57045 NRyo6oGDlA0h1FyJFI TWSG1 7.63 10.58 0 07.02 1 2.4 199870 iqSAkK_1K_x6Efd1UU FAM76A 7.6 13.52 0 0 9.55 1 2.41969 ci7XlTlUtpVN3TX.ow EPHA2 8.15 2.58 0.03 0.06 −4.34 0.01 2.4 7326Tc56SFcOiHRecO_OeY UBE2G1 7.45 12.11 0 0 8.41 1 2.4 1974KoV75wlUkJDXKyr8NU EIF4A2 9.17 2.71 0.02 0.05 −4.12 0.02 2.4 101246tUyy9I3nyO4Sk_Cns ARL4A 7.68 8.98 0 0 5.34 1 2.4 128239ES15d5RLd3vtVE3FQc IQGAP3 8.07 3.69 0 0.01 −2.36 0.09 2.39 29097rkS_KJSIffA018gW4U CNIH4 7.78 4.6 0 0 −0.79 0.31 2.39 HY1m.dEzTJj1jGqlKo8.93 −5.45 0 0 0.61 0.65 0.42 2958 rkkenSKtKBItD9Kp3c GTF2A2 8.03 10.990 0 7.41 1 2.39 54443 f0gC47oTKKQ7uIfqr0 ANLN 7.85 7.33 0 0 3.33 0.972.39 10923 3Tp_7gB4krv78VMu94 SUB1 7.97 6.4 0 0 2.04 0.89 2.39 56984ljHQFHyY4VRLN5dGug PSMG2 8.12 8.13 0 0 4.34 0.99 2.39 f5Kb6DqHXqwOjouG6o8.96 −4.57 0 0 −0.83 0.3 0.42 TeewU1IBpPjvn0b544 7.51 14.57 0 0 10.32 12.39 7443 laDrQERISKKUxIVvQg VRK1 7.71 13.16 0 0 9.27 1 2.39 48029oEnnFVCH5RvveV0jo NFYC 8.33 6.81 0 0 2.63 0.93 2.38 fdyXDoVRATNzB.UVJI8.25 −7.11 0 0 3.04 0.95 0.42 27292 TctET1UxT9u89E9VsU DIMT1L 7.85 6.650 0 2.41 0.92 2.38 90324 HI7XSGoK.iCrSOspqU CCDC97 8.27 −9 0 0 5.37 10.42 57688 E65AL7Uu3fvV9HIgTk ZSWIM6 8 6.83 0 0 2.65 0.93 2.389LPtSjecp3NR5KVe6o 8.91 −5.89 0 0 1.29 0.78 0.42 64837fDRVT1ua6zdUp3E92o KLC2 8.9 −4.34 0 0.01 −1.23 0.23 0.42 64849WCCu6Jmaaeeuee9GWc SLC13A3 8.03 4.39 0 0.01 −1.14 0.24 2.38 147184od3Qq3Rvkk98UilPqU TMEM99 7.58 14.24 0 0 10.09 1 2.37 1408909s.Lqg6Ai_V_QsOCU SFRS12 8.18 4.29 0 0.01 −1.31 0.21 2.37 11846097u.3mlejDnsk9Ktj4 EXOSC6 7.75 4.67 0 0 −0.66 0.34 2.37 3344THlLI4UtELgUfdL5Q0 FOXN2 8.03 5.48 0 0 0.66 0.66 2.36 iHewoL1QMQHzBVJ7rc7.87 8.21 0 0 4.44 0.99 2.36 403244 fX16nuS9A33F4V4_io OR2T35 8.94 −4.90 0 −0.27 0.43 0.42 8570 fXl3eKMCQ9P91RXaV0 KHSRP 7.73 8.83 0 0 5.170.99 2.36 389898 35XRwwT7h.ntC7ItVU UBE2NL 7.75 8.15 0 0 4.38 0.99 2.36144455 ovtEinu7lcR4Uq.sAU E2F7 7.61 9.3 0 0 5.7 1 2.36llGfH57t5ug93Xe1XU 7.52 7.63 0 0 3.72 0.98 2.36 390 xgu_Ce51XwNukoiPCsRND3 7.6 20.83 0 0 13.87 1 2.36 51582 WrkH_LX6fhzEpfgfTo AZIN1 7.76 6.820 0 2.64 0.93 2.35 8821 TE5xJ46f1ULHEhdSKo INPP4B 9.07 −4.62 0 0 −0.750.32 0.42 3315 H6qVIJ5ANY4h5ZQsCU HSPB1 7.9 6.25 0 0 1.82 0.86 2.3555515 0qiV3sT_wM.KgJauqo ACCN4 8.69 −5.86 0 0 1.24 0.78 0.43Zdx1BAdRXxU5SQIeKo 8.99 −5.42 0 0 0.56 0.64 0.43 TI4P7ZfPoZYpSJbuKo 8.83−5.36 0 0 0.46 0.61 0.43 WuJAw1XUXUR1YsJeKo 8.75 −6.1 0 0 1.61 0.83 0.4384262 cNN7k4aoq6BK1aKLbg PSMG3 7.96 2.55 0.03 0.06 −4.39 0.01 2.35 272886z1NPjQRAwOu89qCKo RBMXL2 9.02 −5.14 0 0 0.12 0.53 0.43fpS7owpLCv_LeKI6eo 9.19 −4.66 0 0 −0.69 0.33 0.43 23258QTlqO7TblAxRP176RI RAB6IP1 7.69 7.75 0 0 3.87 0.98 2.34 9519iZLD3TtVMJIntEu5HE TBPL1 7.86 9.13 0 0 5.51 1 2.34 WPjkQLCegA3irp8uok7.58 10.15 0 0 6.59 1 2.34 TNEEISoKYAKlJRQdqo 8.76 −5.36 0 0 0.47 0.620.43 Kpbj6CT4jLesVCgxao 8.98 −4.81 0 0 −0.42 0.4 0.43 cnf_nNV.UWUyqT06Go8.68 −6.03 0 0 1.51 0.82 0.43 BvhWoCe.nOy0msRkqo 8.95 −5.74 0 0 1.070.74 0.43 146547 T5LcfXnXnh3XjUieKo PRSS36 9.17 −5.19 0 0 0.19 0.55 0.43fCkrIgODj6c4ZVX16o 8.95 −5.47 0 0 0.64 0.66 0.43 10927KU.1V0Vwd3z3llEOQk SPIN1 7.72 8.44 0 0 4.72 0.99 2.34 913680hCt0d7ZUpIJECuSz4 CDKN2AIPNL 7.59 6.87 0 0 2.72 0.94 2.33QgJfl0rVYYNeV8N7qo 8.77 −6.36 0 0 1.99 0.88 0.43 QkgydO_aO3.qMJAe6o 8.57−6.73 0 0 2.51 0.92 0.43 Nfk_nIOO_jpRVSC06o 8.96 −5.3 0 0 0.37 0.59 0.436156 Z_qltWdcKSgjrpZAgg RPL30 7.86 5.63 0 0 0.9 0.71 2.33 861crSKWNZIFIG.1XXoe8 RUNX1 7.52 16.88 0 0 11.81 1 2.33 l1wUQ7uRdNMoKBEDqo8.77 −5.31 0 0 0.39 0.6 0.43 9412 oSgRSbyewC_SQ.Ppy0 MED21 7.51 7.44 0 03.47 0.97 2.32 NHSl9HIg9QrtMSc_io 8.9 −5.36 0 0 0.47 0.62 0.43TNIhRUhEIdXknueqyQ 7.81 9.48 0 0 5.89 1 2.32 EXknuzddO6XQCTF76o 9.08−5.7 0 0 1.01 0.73 0.43 uycLILHlK8.KgP8BQQ 7.75 10.2 0 0 6.64 1 2.325573 cuQcHh3vPjV915X9Uo PRKAR1A 8.62 5.43 0 0 0.58 0.64 2.32 26060x4IHYfzuNOs_sxO6ro APPL1 9 −5.19 0 0 0.19 0.55 0.43 54585Wrr_JfjyH.jucJSEpI LZTFL1 7.88 5.59 0 0 0.83 0.7 2.32 8161ESkXp4u56LijfgSAfU COIL 8.12 4.08 0 0.01 −1.67 0.16 2.32 136051Z6ijZeJUqK0KeS4kOM ZNF786 8.41 2.86 0.02 0.04 −3.86 0.02 2.32 169522rSQngp84sxRTGSoiqI KCNV2 8.64 −5.04 0 0 −0.05 0.49 0.43 1138286VRlHVRUIj66DAKgio FAM83F 8.96 −5.57 0 0 0.8 0.69 0.43 2030oHjV5_5KUuinfqfogQ SLC29A1 7.76 4.88 0 0 −0.31 0.42 2.32 7048rplyA9R_RbKk54xTVA TGFBR2 7.88 4.48 0 0.01 −0.99 0.27 2.32 388962Zo_aM.F3tVAZ4UZXp4 BOLA3 8.18 6.43 0 0 2.08 0.89 2.32 6418xU7g3q6jDodJ3t50OU SET 7.81 6.05 0 0 1.53 0.82 2.32 9403fl07nu53_AoOEkhxAk 15-Sep 7.93 8.05 0 0 4.25 0.99 2.31 64778xV6RCA9S07gkE5X_10 FNDC3B 7.68 12.59 0 0 8.81 1 2.31 KOh3bXtFSnouSaZDdo9.79 2.41 0.03 0.08 −4.63 0.01 2.31 246184 ZS3qC7LUvp8ksv2_qo CDC26 8.99−5.48 0 0 0.65 0.66 0.43 23468 ZijmgBAiAgEkCJwKKo CBX5 8.8 −5.48 0 00.66 0.66 0.43 0N6VfLhKKS.5VIKVYc 8.15 −7.06 0 0 2.97 0.95 0.43 653573Bk9InECgygLKsu_j3o GCUD2 7.96 5.3 0 0 0.36 0.59 2.31 5991Bjr0kenz.vM_Dkopqo RFX3 8.85 −6.09 0 0 1.59 0.83 0.43 51125ZKNqnnzl.b81_q.iJk GOLGA7 7.78 6.81 0 0 2.63 0.93 2.31 61619t9J9_lB8v5RIj73.k RPL32 8.2 −8.01 0 0 4.2 0.99 0.43 25790cJ4mQJwTXlJxd7geKo CCDC19 9.07 −4.72 0 0 −0.57 0.36 0.43 4144i65p6U6ICeH6eu6xIg MAT2A 8.1 4.72 0 0 −0.58 0.36 2.31 23023Kgo4n_6QkA0kh5eEqo TMCC1 8.99 −5 0 0 −0.11 0.47 0.43 511230TVTvweER6qdL7uew4 ZNF706 7.78 6.59 0 0 2.32 0.91 2.3 9225996pV17lCrGzPuCwJdE MRPS36 7.59 6.68 0 0 2.44 0.92 2.3 10269HqNB7GX_s3hTAt.51k ZMPSTE24 7.73 9.64 0 0 6.06 1 2.3 rueRfRt4ukvsM4KoIo8.6 −5.67 0 0 0.95 0.72 0.43 57590 ijOuV7s1SI5yAHvf50 WDFY1 7.96 3.170.01 0.03 −3.29 0.04 2.3 Zrot0pPh9UrgoKuP_o 8.9 −4.13 0 0.01 −1.59 0.170.43 8771 fIkI3bX18hIpSSoe6o TNFRSF6B 8.75 −5.92 0 0 1.34 0.79 0.43 811NV1BeqpLruiCUSl4j8 CALR 7.63 6.11 0 0 1.62 0.83 2.3 KQemKt_559N0yoC6Co8.78 −5 0 0 −0.11 0.47 0.44 91408 o10FHdcd_l_BcXer6M BTF3L4 7.73 18.21 00 12.57 1 2.3 4154 lNSX0dSevADvkfNJBU MBNL1 7.99 6.14 0 0 1.66 0.84 2.29389641 QRT9ETXiXU_.4tJ7b0 LOC389641 7.62 16.1 0 0 11.33 1 2.29 109450.cj6oyogKilSgrdV4 KDELR1 7.59 5.73 0 0 1.05 0.74 2.29 9364NnjnUboP3fkB5MIsdU RAB28 7.89 5.42 0 0 0.56 0.64 2.29 57727xIKKv3p7r3A6JVKCeU NCOA5 7.53 8.89 0 0 5.24 0.99 2.29 27257NroEkhQnoJIgvgLkpU LSM1 7.47 12.54 0 0 8.77 1 2.29 HCgEhEXkS_gOiDgjEM 810.36 0 0 6.81 1 2.29 2026 T5vrUiaKe7l6qL.Xcw ENO2 7.81 4.96 0 0 −0.180.46 2.29 9662 clf.Luzyjup6.n.cUU CEP135 8.1 3.69 0 0.01 −2.36 0.09 2.29rteiuy6IkugORQojio 8.85 −4.4 0 0.01 −1.12 0.25 0.44 TYhQiS484OkLpCAaro8.51 −5.59 0 0 0.84 0.7 0.44 627 Efnut3_6SC79OTpJKU BDNF 7.75 10.23 0 06.67 1 2.29 92703 6k.AKLpXv97vAFU.rk TMEM183A 8.06 3.93 0 0.01 −1.940.13 2.29 cnKTyrAwxMI2nqbrp0 7.89 4.11 0 0.01 −1.62 0.17 2.29 3806jt6JSj760.h05fgk ACAT1 7.55 10.87 0 0 7.3 1 2.29 39I0p13cP6OOtDkKKo8.74 −4.84 0 0 −0.38 0.41 0.44 3491 cLA6ipPU1fXgqoR1OI CYR61 8.23 3.88 00.01 −2.04 0.12 2.29 xJUiIBlXaAVZ3V3JIA 8.22 −7.78 0 0 3.92 0.98 0.449474 xEhAFLtKX_Syn4uB94 ATG5 7.96 9.17 0 0 5.55 1 2.28 833433obrCQopAnZlAmA1Y HIST1H2AC 7.73 5.2 0 0 0.2 0.55 2.28 51655ZtKFRqk837e49avnuE RASD1 7.62 7.49 0 0 3.54 0.97 2.28 3336Nkixi3imiosOkoQm.I HSPE1 7.85 5.89 0 0 1.3 0.79 2.28 28969EA6JXik0nPMfqHcXdE BZW2 7.86 10.16 0 0 6.61 1 2.28 158160rwyeruuk5k7LVBx0oo HSD17B7P2 8.21 3.1 0.01 0.03 −3.42 0.03 2.28QTx_4Pn7NQDkhEOeqo 8.81 −7.06 0 0 2.97 0.95 0.44 3T9SoLQjRACquPeuqo 8.61−5.38 0 0 0.5 0.62 0.44 1958 Ebfrl.7uOZfnjp_E7k EGR1 8.37 2.95 0.01 0.04−3.69 0.02 2.28 9480 oXuDF0n0HqXUxLS_uo ONECUT2 8.79 −5.15 0 0 0.13 0.530.44 WlG0AfeJSmAyAiq1yo 8.86 −4.47 0 0.01 −1 0.27 0.44WVCDnpVQ3UAvyuC9ao 9.05 −5.37 0 0 0.49 0.62 0.44 6908 f_5HiBFmSbh7i_dMW4TBP 7.74 7.66 0 0 3.76 0.98 2.28 91298 BjSoBf6h94Sk3rgiEM C12orf29 7.7710.97 0 0 7.39 1 2.28 7594 Q3CmaEfSE8RwNLnCxI ZNF43 8.1 −10.98 0 0 7.4 10.44 0tnVvUrZokCtjRvdjQ 7.62 10.93 0 0 7.36 1 2.28 7324Newpugyi_dLo_vc77o UBE2E1 8.12 3.2 0.01 0.03 −3.25 0.04 2.28NMdClq5rp0xE6JCgoU 7.82 4.6 0 0 −0.78 0.31 2.27 T_XgCX1mqPwZP61Cqo 8.72−5.81 0 0 1.17 0.76 0.44 5480 i4S65HUyJ1CQeOpOFs PPIC 7.7 9.09 0 0 5.461 2.27 51635 N7pDE5QXqXrowUEI6o DHRS7 8.87 −4.33 0 0.01 −1.24 0.23 0.44123811 KdWqh_v9tQo76S6EfI C16orf63 7.64 10.5 0 0 6.94 1 2.27 3093xtPfn5H1XPhE4Ce764 UBE2K 7.71 5.53 0 0 0.73 0.68 2.27 143903EGF176FVG.6ezX81SU LAYN 7.53 10.06 0 0 6.5 1 2.27 57198ZoOoiqC36SoDV.6URI ATP8B2 7.73 4.37 0 0.01 −1.17 0.24 2.27 1399HtXEooEul_ffIa30e4 CRKL 7.97 8.09 0 0 4.29 0.99 2.27 83941Zfo6_okjY.xfoxXn_o TM2D1 8.02 9.35 0 0 5.76 1 2.27 56942ZqSpvyx7dV.FJAXh9E C16orf61 8.01 3.22 0.01 0.03 −3.21 0.04 2.27 25862N1ycfqKeK6iD50JUos USP49 8.4 2.82 0.02 0.04 −3.92 0.02 2.27 10049EXn.T7t4DuJRsu2154 DNAJB6 8.01 6.5 0 0 2.18 0.9 2.27 1613940ulgB09G0HnQF1dI6o C14orf174 8.87 −6.06 0 0 1.54 0.82 0.44 5500xnlXiCIfDUJePscuk0 PPP1CB 7.75 9.41 0 0 5.81 1 2.26 64326WV1.OF.qE_oMVJQd1E RFWD2 7.64 8 0 0 4.19 0.99 2.26 2920N244TNE7SUe4yKeKDU CXCL2 7.4 13.35 0 0 9.42 1 2.26 27242rArpuh1f7urqv7qy64 TNFRSF21 7.88 4.2 0 0.01 −1.47 0.19 2.26 6208Q76eVKO6VIrkKJ6s0U RPS14 7.67 4.42 0 0.01 −1.09 0.25 2.26 92879UX786Sv30derc466o TAAR2 8.9 −4.36 0 0.01 −1.19 0.23 0.44 4686ZeOr8VJxUskwf9Enao NCBP1 9.41 −4.5 0 0.01 −0.95 0.28 0.44 6259H_Rcgy5zkSJq5_L77Y RYK 8.05 3.8 0 0.01 −2.17 0.1 2.25 5366Nr2A51_0Ty7k1xAC40 PMAIP1 7.75 11.9 0 0 8.24 1 2.25 201965E7Kr3rjrrF3zxfOwBE RWDD4A 8.85 4.49 0 0.01 −0.96 0.28 2.25 10094HklFt1IlepJP9SQjsQ ARPC3 7.72 4.41 0 0.01 −1.1 0.25 2.25 84928TFuzS7yO5NW.7T1dIc TMEM209 7.87 7.9 0 0 4.06 0.98 2.25 148534197_QDfV4veBUkU0sU TMEM56 7.68 6.51 0 0 2.2 0.9 2.25 0h1OAuTzRgng.uwk_47.81 5.13 0 0 0.09 0.52 2.24 6611 ike2dzggSeqZez7Xug SMS 7.75 9.76 0 06.19 1 2.24 5725 EgHXV_3JXu9nuhnsik PTBP1 7.85 3.32 0.01 0.02 −3.02 0.052.24 23760 leyzT6ifKZE6A4iVpk PITPNB 7.94 4.35 0 0.01 −1.21 0.23 2.2423517 cgpJMPb7OKZegg_fYQ SKIV2L2 8.17 −5.67 0 0 0.96 0.72 0.45 10627ZPwXFJX3VUMHutzEi0 MRCL3 7.83 8.12 0 0 4.34 0.99 2.24 84988ix7EoR6Vd0rSCE5eio PPP1R16A 8.87 −4.49 0 0.01 −0.97 0.27 0.45 51588B.UV.5enXpF7F3od1w PIAS4 7.63 5.71 0 0 1.02 0.73 2.24 8869reEHuCUV6nEgFEt9Uk ST3GAL5 7.48 7.85 0 0 4 0.98 2.23 9404WRv9U.le6dHt8Q0ee4 LPXN 7.45 8.38 0 0 4.65 0.99 2.23 2764TlKkvVHj8jrUIw3T0o GMFB 8.61 3.01 0.01 0.04 −3.59 0.03 2.23Q_L6DqAw_l7i4d_oio 8.6 −5.42 0 0 0.56 0.64 0.45 10560 TYTHT_vwkoNcgkDo6oSLC19A2 9.05 −5.88 0 0 1.28 0.78 0.45 55437 KntX6g6ldIoS59QsTc ALS2CR27.53 11.94 0 0 8.27 1 2.23 160897 oO3ZwwVSc_3vu9J4jk GPR180 7.53 13.75 00 9.73 1 2.23 1457 KuoAcwHd_8SVZRV_e4 CSNK2A1 7.75 5.83 0 0 1.2 0.772.22 51341 WMhneeR4h9_0OVBaao ZBTB7A 8.68 −4.26 0 0.01 −1.37 0.2 0.45lgGKciOMLnrp6vuqio 8.95 −5.27 0 0 0.32 0.58 0.45 90799rV1c4pSH4wyyuCveik CCDC45 7.83 7.8 0 0 3.94 0.98 2.22 8683WVRHH3df0pXHiErjqA SFRS9 7.95 3.11 0.01 0.03 −3.4 0.03 2.22 79412xoSgE3rnPN6h_l4W6o KREMEN2 8.83 −4.69 0 0 −0.63 0.35 0.45 80219ZJx.1LL_Uf3WKy.p50 COQ10B 7.74 7.99 0 0 4.17 0.98 2.220ZIir9WP4BOSAKhPqo 8.7 −5.06 0 0 −0.02 0.5 0.45 EU0eeLoSKoiCOq.iuo 8.99−4.98 0 0 −0.14 0.46 0.45 51306 ipJHzne4Sz7u0y_JLI C5orf5 7.86 5.54 0 00.75 0.68 2.22 5876 9aqj_SEpSiM66Nf9MU RABGGTB 8.05 5.48 0 0 0.66 0.662.21 57158 xEO15CGnOkWIXOeOio JPH2 8.95 −4.68 0 0 −0.64 0.35 0.45 27399ud_nfqeixbrikosBHI GLO1 7.54 10.12 0 0 6.56 1 2.21 79738Ql3u3Sd7vJc7vyqKv8 BBS10 7.97 6.75 0 0 2.54 0.93 2.21 93269pfxaT47p079KSH6rU ZNHIT3 7.68 14.65 0 0 10.38 1 2.21 91894f0r1IXwSEDqoKqeKbo C11orf52 8.77 −5.49 0 0 0.67 0.66 0.45 1129cjfMdel0LjXXl0t1AI CHRM2 9.11 2.45 0.03 0.07 −4.56 0.01 2.21 60412B5Hh6lE34AdugKgKoo EXOC4 8.63 −5.27 0 0 0.32 0.58 0.45THwCseKTqVQ6DTzV6o 8.73 −5.28 0 0 0.35 0.59 0.45 6322 KeyPr9TEqC91tc5Dv0SCML1 7.62 8.11 0 0 4.32 0.99 2.21 1389 0SXn903sACqoowf0So CREBL2 9.11−3.26 0.01 0.03 −3.14 0.04 0.45 152002 3XXsbKeSG4CVSq1P7M C3orf21 7.648.25 0 0 4.49 0.99 2.2 115294 03JNI0NUINTSQXSFBU PCMTD1 8.09 4.94 0 0−0.21 0.45 2.2 r56n1SL949LK9riiSo 8.86 −5.47 0 0 0.65 0.66 0.45 25853fhJC1FcH7xEkTFEr3o WDR40A 7.52 9.68 0 0 6.1 1 2.2 64279Vj517sCOX7bkgEDp4 SFRS2 8.91 3.02 0.01 0.03 −3.57 0.03 2.29v_itOuoo0XilKL_KU 8.27 2.81 0.02 0.05 −3.94 0.02 2.2 6741BnlSXq3rAoAsS.SpCA SSB 7.9 8.09 0 0 4.3 0.99 2.2 0ug6VOXstUnHainSSQ 9.472.24 0.05 0.1 −4.93 0.01 2.2 KcPUJwL65sl6S7uKLU 7.46 11.44 0 0 7.82 12.2 9roOqLqirMmr3zPC_o 9.36 −2.64 0.02 0.06 −4.23 0.01 0.45 1528169VIIIdSIoJ03igJ4io C4orf26 8.64 −5.31 0 0 0.39 0.6 0.45 6884Bm5y6jpI4oIIVRv4oI TAF13 7.51 13.91 0 0 9.84 1 2.2 9898H5zqV5H1.n1170V664 UBAP2L 7.75 4.69 0 0 −0.63 0.35 2.2 648Q62B_u7vTRU0vP7irs BMI1 8.08 2.96 0.01 0.04 −3.68 0.02 2.2 51029HiiPQRRISeSh2M1On0 FAM152A 7.83 5.91 0 0 1.32 0.79 2.2 8487fp09Hj2kn5CCud4Lik SIP1 7.63 11.75 0 0 8.1 1 2.2 569933g1c7OIoqKSnkn0lEg TOMM22 7.64 5.23 0 0 0.26 0.57 2.19 64324ogOC6GkkOACSV91SVU NSD1 7.56 14.54 0 0 10.3 1 2.19 221662Eom6S6sA66EpFAnP90 RBM24 7.66 12.88 0 0 9.05 1 2.19 6845ip06xe99zUBf0PTnF4 VAMP7 7.71 11.34 0 0 7.74 1 2.19 201725314xQjiCOncNJ4hJFI LOC201725 7.66 9.49 0 0 5.9 1 2.19 23512rd4._XejLI3Ym.N2p8 SUZ12 7.85 4.58 0 0 −0.82 0.31 2.19 2316703kIj3koHq7kRrvslI EFR3A 8.07 3.06 0.01 0.03 −3.49 0.03 2.19 7901605GRvqiC2lfqN.d_LQ DDA1 7.73 5.97 0 0 1.42 0.8 2.19 iqLvKA4QLopJE7_uqo8.62 −5.02 0 0 −0.08 0.48 0.46 29968 Ek9TyQi_xVdVLfZfXc PSAT1 7.47 14.520 0 10.28 1 2.19 7170 N6fAOx3X.O63f6pY_o TPM3 8.86 2.71 0.02 0.05 −4.110.02 2.19 0HelXOmuilLH_QBRgE 8.04 4 0 0.01 −1.82 0.14 2.19 9231QeyHPdCs8HZIV3qrKo DLG5 8.77 −6.97 0 0 2.84 0.94 0.46 4610ifPek3yF1EVuIDXoio MYCL1 8.9 −4.78 0 0 −0.48 0.38 0.469VKA3NT6p_LoLjqrCo 8.82 −5.46 0 0 0.62 0.65 0.46 6598302.s3vpcuhJ7l65F3o GRAMD3 8.26 4.67 0 0 −0.67 0.34 2.19NUEsrgJ8kucTvT9Emo 8.91 −4.69 0 0 −0.63 0.35 0.46 5430xB8qsvXnuLrxJ412oI POLR2A 7.89 3.42 0.01 0.02 −2.86 0.05 2.19635TNDQHzIiEDHqmqo 8.49 −5.9 0 0 1.31 0.79 0.46 55973 BU_IInUUkheOXOBERIBCAP29 7.79 8.37 0 0 4.63 0.99 2.19 343413 xIF0CKLglK3ni9FuqI FCRL6 8.65−5.34 0 0 0.44 0.61 0.46 22806 ihNn9f60K_kiQqzAqo IKZF3 8.63 −7.09 0 03.01 0.95 0.46 94107 KlKvi1atqlqo_WmTSo TMEM203 9.03 −3.49 0 0.02 −2.720.06 0.46 1843 EkgiAodLu41r9._dlU DUSP1 7.62 7.56 0 0 3.63 0.97 2.18147339 iOR_kvDo3nvnou4m6E C18orf25 7.63 13.1 0 0 9.23 1 2.18 9631ud5ejnv7rxfvidS3OI NUP155 8.39 −8.88 0 0 5.22 0.99 0.46 819ZrdJSVyIeffu.u097U CAMLG 8.5 4.89 0 0 −0.29 0.43 2.18 rNJREExcHLrf6TlSuo8.82 −6.11 0 0 1.61 0.83 0.46 134492 KmjX6uQhQOSICfE8iI NUDCD2 7.5311.78 0 0 8.13 1 2.18 frfk._kxUkLOxChk6o 8.89 −5.11 0 0 0.06 0.52 0.4655320 6fhMoz.V3pxE9FxX70 C14orf106 7.8 6.56 0 0 2.28 0.91 2.18 84992En_ZM0p8oe6inwvkjk PIGY 7.69 8.75 0 0 5.08 0.99 2.18 6303EpBIouKLnnsjhBdT3M SAT1 8.34 6.8 0 0 2.61 0.93 2.17 Tlmcdek7o0UIxD96147.97 5.93 0 0 1.35 0.79 2.17 51259 T4kaIl0766v1IuO4CU MGC13379 7.57 7.750 0 3.87 0.98 2.17 9903iU_Col3Td1FiKo 8.62 −5.01 0 0 −0.1 0.48 0.4610463 6vSskuJPvTOIOmnq40 SLC30A9 7.94 6.42 0 0 2.08 0.89 2.17 2054KqF5dW47VF.X0K3tM4 STX2 7.86 5.34 0 0 0.43 0.61 2.17 KK8G73dR7vnXqI6IKo8.9 −4.69 0 0 −0.63 0.35 0.46 27131 xcOlnqq4qa7vs7f6u8 SNX5 8.3 2.260.04 0.09 −4.88 0.01 2.17 cYK0pDEsrIu8p6ogJo 8.53 −5.87 0 0 1.27 0.780.46 65991 lXn1UR3l3XhN6t3q84 FUNDC2 8.11 −8.75 0 0 5.08 0.99 0.46 10929rniefXv994_deqAEZc SFRS2B 7.78 8.16 0 0 4.38 0.99 2.17 55970TkeV81_7Tef.b3mM5U GNG12 7.77 10.62 0 0 7.05 1 2.17 QbvcDk5F4sAo3qeS3I7.5 11.6 0 0 7.97 1 2.17 TRo0eSXUXVL0ID3Tt0 8.12 2.95 0.01 0.04 −3.690.02 2.16 29068 BTrREwL5LygKjqSoAE ZBTB44 7.82 6.22 0 0 1.78 0.86 2.16in1cVdGmFxJCLNAgEI 8.12 −7.4 0 0 3.42 0.97 0.46 6830 xQlP_B95XRaHep7h6oSUPT6H 8.88 −4.67 0 0 −0.67 0.34 0.46 3l_CD7lFRedRyDl4B4 8.13 −7.27 0 03.25 0.96 0.46 opUM.FCiF9d3ljrWio 8.53 −6.48 0 0 2.16 0.9 0.46 4193QVV9TRPkEjvqV9uIPo MDM2 7.71 7.85 0 0 3.99 0.98 2.16 6Sd7n55t.4kPRcF3UI8.09 −5.75 0 0 1.08 0.75 0.46 6138 QrxUd7UdUynEgAtEJk RPL15 8.18 3.81 00.01 −2.16 0.1 2.16 64065 oep3NMyEp94y.kHsJI PERP 8.05 3.35 0.01 0.02−2.97 0.05 2.16 cx3O_VLnobkOnuN2Z0 8.05 2.47 0.03 0.07 −4.53 0.01 2.16Nfp52erfo7avYUfpY4 8.23 2.45 0.03 0.07 −4.57 0.01 2.16KU01y6gcB_N8qOMCFY 7.53 11.76 0 0 8.11 1 2.16 ckgBTieA3cSgUueqyo 8.83−5.41 0 0 0.54 0.63 0.46 51317 3tLitW4t.uLX7tNvak PHF21A 8.07 4.31 00.01 −1.28 0.22 2.16 169200 uXr46X666D.v0lIpx0 TMEM64 7.92 8.57 0 0 4.870.99 2.16 fuy06IIuvlI7zOqgqo 8.51 −5.14 0 0 0.11 0.53 0.46 32296I55cEvV10ClF_ue6o HOXC13 8.89 −4.93 0 0 −0.22 0.44 0.46 54836Nwv1cXjpVd4TAeRF6o BSPRY 9 −4.78 0 0 −0.47 0.38 0.46 3015oHcEntS7649S6Hs3e4 H2AFZ 7.6 6.61 0 0 2.35 0.91 2.15 3516lTFK4xz0AFW_3V5C54 RBPJ 7.78 5.4 0 0 0.54 0.63 2.15 3646uJK0inXB6kHQj3p9x4 EIF3E 8.59 2.75 0.02 0.05 −4.04 0.02 2.15f0TO9M5Vzv6qzR0v9U 7.58 9.9 0 0 6.34 1 2.15 EoF7BzxdM6QCof6o6o 8.55 −5.90 0 1.31 0.79 0.46 3189 ZkrzZCO3yLKvCvdLhE HNRPH3 7.62 7.25 0 0 3.220.96 2.15 8773 Tk3gR9AntLuz6.RQwU SNAP23 7.7 7.25 0 0 3.22 0.96 2.15ETPlWZcy.7wt8V7D.4 7.7 10.19 0 0 6.63 1 2.15 23560 Q_wieokBG.OLu2g1bkGTPBP4 7.81 4.52 0 0.01 −0.92 0.28 2.15 6382 0HmH95ei7OHkTh2quo SDC18.73 −4.99 0 0 −0.13 0.47 0.47 10135 WbfQoVL541QQCtQAqU NAMPT 7.44 10.430 0 6.87 1 2.15 286148 N5KS7F0r4d7E3gy4tE DPY19L4 8.19 4.46 0 0.01 −1.010.27 2.15 618 rooyfiVKL2IXl6kMyY BCYRN1 8.83 2.42 0.03 0.08 −4.61 0.012.15 79053 rcXn6Xql3oLee4P7PU ALG8 7.74 6.49 0 0 2.17 0.9 2.15 29942H4qqKjD9BUeXfFIBP8 PURG 8.19 −5.06 0 0 −0.02 0.49 0.47 9184lSy3hs.Vfe1XLCVL54 BUB3 9.35 2.41 0.03 0.08 −4.64 0.01 2.14 4233Bt3FKtCJOBk0MgIHao MET 8.9 −6.22 0 0 1.79 0.86 0.47 54379ppN.B6XUdDqAeHZe4 POLR2H 7.65 6.2 0 0 1.76 0.85 2.14 Nq6KpKKhA6I4NTwA_o8.75 −4.15 0 0.01 −1.55 0.18 0.47 0PYCACDlDOACICSAiA 8.09 −6.62 0 0 2.360.91 0.47 201633 EAyod9cqgAqqeouMio VSTM3 8.62 −5.46 0 0 0.63 0.65 0.47leHovS65ARJ3dRBd_o 8.59 −5.47 0 0 0.64 0.65 0.47 7117 upUK7Xkp7Dkvw0i5T8TMSL3 10.1 2.82 0.02 0.04 −3.92 0.02 2.14 84447 ulIdet.UvyAKd7lCio SYVN18.75 −5.92 0 0 1.33 0.79 0.47 56957 ZUqFwiAskqgr_u7qro OTUD7B 8.63 −5.650 0 0.93 0.72 0.47 4735 H_cuHCVZM7i4Cx9KRk 2-Sep 8.11 2.44 0.03 0.07−4.59 0.01 2.14 51528 TESrDPN5xHoKWcoJXY C14orf100 7.83 9.58 0 0 5.99 12.14 253260 xGecTP6K967_ytHgSE RICTOR 7.92 6.81 0 0 2.62 0.93 2.14WFHk7A3uozJwJHnyqI 8.37 −4.74 0 0 −0.55 0.37 0.47 23484fkece.zUfpRIf.cEnk LEPROTL1 8.01 4.17 0 0.01 −1.52 0.18 2.14 27738nxvNxSJFup7x_X4s AMY1B 7.8 5.13 0 0 0.09 0.52 2.14 1774oHqHSBUEEqEgh0ZX6o DNASE1L1 8.57 −5.75 0 0 1.07 0.75 0.47 51304Q_CiuuOujIrgorKi5U ZDHHC3 7.97 2.4 0.04 0.08 −4.65 0.01 2.13 79768Be4.iK4vPwilL.ShOo C15orf29 8.78 5.52 0 0 0.72 0.67 2.13 8766x_3fmudOO7qkRoKT54 RAB11A 8.16 4.77 0 0 −0.5 0.38 2.13 55837TVLTuR4O9R4LpLcYQo EAPP 7.57 14.07 0 0 9.96 1 2.13 51083x4v3t.fk3QIpa5XYWU GAL 7.53 14.05 0 0 9.94 1 2.13 0uwlcH3gpHzS3SnKqI8.68 −5.55 0 0 0.77 0.68 0.47 0bECSHlZA2FrrAkVKA 7.83 6.16 0 0 1.69 0.842.13 285671 lYKbgI6cSCSrAx0ouo RNF180 8.71 −4.92 0 0 −0.24 0.44 0.4756672 fl..B_KuyK11Gfv5eA C11orf17 7.87 5.48 0 0 0.65 0.66 2.13 6119Z3eg_6C6_giwWUKUU0 RPA3 7.68 12.47 0 0 8.72 1 2.13 6iiQn4jA_8MPPvtS6o8.73 −4.9 0 0 −0.29 0.43 0.47 95SVw6USP94Y8sLPz0 7.9 7.31 0 0 3.31 0.962.13 TJItHkgl6NfkwX7Yuo 9.09 −3.6 0 0.02 −2.52 0.07 0.47ov6sop_dyss.4KClSo 8.86 −4.03 0 0.01 −1.76 0.15 0.47 rvuijuoIHSDVDEycuo8.63 −4.61 0 0 −0.77 0.32 0.47 60481 udET_KS60BKwJc47u0 ELOVL5 7.84 4.150 0.01 −1.55 0.18 2.12 4267 opTzwrXsHQO0FUWKRU CD99 7.53 8.37 0 0 4.630.99 2.12 9076 Zuc3vS45XSJ357yekk CLDN1 7.51 16.24 0 0 11.42 1 2.1255532 HmgCRr0V9CIEksod6o SLC30A10 8.84 −4.64 0 0 −0.72 0.33 0.47 911BkIOUr766n4cQErOKo CD1C 8.61 −3.67 0 0.02 −2.41 0.08 0.47lr8kqE4rof_H6snvQ4 7.77 8.4 0 0 4.67 0.99 2.12 u4dX8Dt1ICUMA4jIio 8.71−5.19 0 0 0.19 0.55 0.47 Nl9A0UHu0FB5d8_X54 8.03 −7.03 0 0 2.92 0.950.47 9cwWXXRJunW5.v7sqo 8.79 −5.28 0 0 0.34 0.58 0.47 57826No2Sg0qgLj.Arr91JE RAP2C 8.07 7.66 0 0 3.76 0.98 2.12 0iTXhh1P196dVES3xE8.03 −6.12 0 0 1.64 0.84 0.47 uopIhU54vp4iNLJQno 7.68 7.35 0 0 3.36 0.972.12 2957 u..VQ35rj_rRXWrvMs GTF2A1 7.45 4.98 0 0 −0.15 0.46 2.12 2258TmCOYpTxe.jV7aAXpE FGF13 8.14 −6.59 0 0 2.32 0.91 0.47Qi_4HrqWzsEnhQbgjE 10 2.41 0.03 0.08 −4.64 0.01 2.11 2697Wi_JLf_i4UkH_O.kcI GJA1 7.59 13.75 0 0 9.72 1 2.11 10672NiCtd68t3QPinvyoDU GNA13 7.7 7.55 0 0 3.61 0.97 2.11 135d4NwRAbp8vfkgkk7.95 −7.71 0 0 3.83 0.98 0.47 KgR4AvymnirntuAsqo 8.66 −4.8 0 0 −0.450.39 0.47 3998 NBeUcT3r8Ty8fTnp6o LMAN1 8.97 −5.04 0 0 −0.04 0.49 0.47644914 f7pnW4DyG80gtR4H3o LOC644914 7.56 7.67 0 0 3.77 0.98 2.113dUD1VNX3oikISLS6o 8.68 −4.89 0 0 −0.3 0.42 0.47 ogG4U9fq9fTuojkh6k 8.11−7.63 0 0 3.72 0.98 0.47 55207 WooPoHIO7h3uqHkyv4 ARL8B 8.22 2.43 0.030.07 −4.61 0.01 2.11 1973 02tiuhr_lsCu6c8E64 EIF4A1 7.44 4.91 0 0 −0.260.44 2.11 xuQ04dHkl0B14nQuNc 8.65 2.6 0.02 0.06 −4.31 0.01 2.11 5033QXkwQR6l98HAOdFHyU P4HA1 8.07 4.32 0 0.01 −1.26 0.22 2.116TXndBzBPppp6kildc 7.5 7.22 0 0 3.19 0.96 2.11 4001 QqKsDAUe5t_uw.gj5ULMNB1 7.75 5.96 0 0 1.4 0.8 2.11 9553 HHlSu60U713Wa33_UI MRPL33 7.577.73 0 0 3.85 0.98 2.11 3.VCCdEjf9ScTXniKo 8.66 −4.61 0 0 −0.77 0.320.48 HK6nVduR.Pl6kv_fjc 7.84 4.81 0 0 −0.42 0.4 2.1 58517KEReiKE.gBHvfFdgV4 RBM25 7.98 5.03 0 0 −0.06 0.48 2.1 50831BkA6hCdSI1BR4pUQio TAS2R3 8.71 −5.29 0 0 0.35 0.59 0.48ifeztLST8OFFx7uRJE 7.71 4.78 0 0 −0.47 0.38 2.1 BdPveyIyAM2RTKKqIo 8.48−5.72 0 0 1.03 0.74 0.48 3fYBMgAaDHiN66qlpo 8.17 −4.81 0 0 −0.43 0.390.48 195827 cntX1SX_KLyoJMCqn4 C9orf21 7.4 11.96 0 0 8.29 1 2.1Knkg_KupfIXrO6KIg4 7.59 13.12 0 0 9.24 1 2.1 9373 oOeyPzXA.nskuqCKhoPLAA 8.64 −5.34 0 0 0.44 0.61 0.48 55330 rl7t9Sdw0gJ5_2Kk6o CNO 8.87−3.85 0 0.01 −2.07 0.11 0.48 9enQrQIwqeqr6N6feo 9.12 −2.89 0.01 0.04−3.8 0.02 0.48 8890 Qvexe_9xi0IkuFLhqo EIF2B4 8.73 −5.85 0 0 1.23 0.770.48 0TgoKQkv0WjLhMU2UU 7.51 10.56 0 0 6.99 1 2.09 5062iWC39U9H3cgJ5QhIpI PAK2 7.89 5.18 0 0 0.17 0.54 2.09 WerLIDdICKiAwA6oqo8.57 −5.32 0 0 0.41 0.6 0.48 10289 NeUv3for6T7AooEnwo EIF1B 7.46 10.96 00 7.38 1 2.09 64430 QH4ofdRFVPSOXiBJwk C14orf135 7.82 6.49 0 0 2.18 0.92.09 400509 QieqL0IUl6kEw4j9J0 RUNDC2B 8.36 2.48 0.03 0.07 −4.51 0.012.09 10178 cCCnkIqoIqjypOhIKo ODZ1 8.49 −5.95 0 0 1.38 0.8 0.48 940810oqa16BQk1GjHiq4T8 SFXN1 7.56 7.68 0 0 3.78 0.98 2.09 Hl6BOmsEH3T.Q_PR6o8.81 −5.02 0 0 −0.08 0.48 0.48 6801 ESe9EwJF6QJP8XvKqI STRN 8.73 −5.02 00 −0.07 0.48 0.48 2009 BkjiHsv5I6boJPTSqI EML1 8.58 −5.31 0 0 0.39 0.60.48 TX6ABK4gejICTsUjio 8.79 −4.62 0 0 −0.74 0.32 0.48 9782HpTDXI5GfcPTsXkTuE MATR3 8.73 2.75 0.02 0.05 −4.04 0.02 2.08 5239jjkvez8_57t61wuiU ATP6V1A 8.08 3.99 0 0.01 −1.84 0.14 2.08 6917HCAgXkPE2SBJXikIgg TCEA1 7.53 9.64 0 0 6.07 1 2.08 389674cA.6KSCd6VU666KUsc HNRPA1P4 7.98 3.26 0.01 0.03 −3.13 0.04 2.08 8365NGR38afa6cKdefnkd8 HIST1H4H 7.6 5.4 0 0 0.53 0.63 2.086jh6c.oAXq5x5Qers0 7.67 9.15 0 0 5.53 1 2.08 143187 lks.ysTbiOol5PVKqYVTI1A 8.62 −5.27 0 0 0.32 0.58 0.48 cTs7slK10AOyBIijio 8.57 −5.14 0 00.12 0.53 0.48 oj53EpP3p1uNU4XQKo 8.86 −4.65 0 0 −0.7 0.33 0.48 9559TjqodKKF7gk7Lzcjeo VPS26A 7.79 12.08 0 0 8.39 1 2.07 103910NfdIR9VRXTIF75OQfI MRLC2 7.62 8.67 0 0 4.99 0.99 2.07 rAPOk5b8kgeCOoI.NI8.25 −4.94 0 0 −0.22 0.45 0.48 142 uFAn28g7eXx6.VSoKA PARP1 8.15 3.410.01 0.02 −2.87 0.05 2.07 54453 TUv5K5EBzirfs1GwRI RIN2 7.65 6.94 0 02.81 0.94 2.07 H6dQAFfgAgFZW1Q16o 8.52 −5.02 0 0 −0.09 0.48 0.48 6399TnqJL5KUS4Lu_fe0fw TRAPPC2 7.45 7.55 0 0 3.62 0.97 2.07 796503KT3iqQbooKlKjk6j8 C16orf57 7.76 6.05 0 0 1.53 0.82 2.07TJEoiL6ciul9_Iokuo 8.91 −4.67 0 0 −0.66 0.34 0.48 27075WukXoPx7PT7ake1Huk TSPAN13 8.04 7.72 0 0 3.84 0.98 2.07Nv6rtD.c0GQEXyrFSE 7.77 5.34 0 0 0.43 0.61 2.06 K3SOEdMkRF34UkgJRI 8.02−7.42 0 0 3.44 0.97 0.48 7414 HVr31Lr_IR6.Efzlo4 VCL 7.67 7.48 0 0 3.530.97 2.06 134553 B5HriTdePUfH.dXuBI C5orf24 7.55 9.59 0 0 6.01 1 2.0693487 iTV_PXV47rAekR1Krc MAPK1IP1L 7.97 9.14 0 0 5.52 1 2.06 10653xp59et6So6v5.oDXco SPINT2 8.63 2.91 0.01 0.04 −3.76 0.02 2.06 700904TlFWDp0f0eKOe13g TEGT 7.88 3.9 0 0.01 −2 0.12 2.06 3stASAIQeJJA0kBDAU8.09 −5.94 0 0 1.36 0.8 0.49 9867 iJUrcDsOvr8_9zBVJU PJA2 8.44 2.68 0.020.05 −4.17 0.02 2.06 7157 ce4DnpP5FxdEi5PuKs TP53 7.7 7.58 0 0 3.65 0.972.06 160287 9Sq4lHuXpfJ.j8s1I4 LDHAL6A 7.93 3.97 0 0.01 −1.87 0.13 2.060SXouANerHh.iKLi7k 7.79 7.47 0 0 3.51 0.97 2.06 Qh4KuYuereTu.f1NKo 8.48−5.44 0 0 0.59 0.64 0.49 57495 lQjITr15XQifS7Irio KIAA1239 8.72 −4.17 00.01 −1.52 0.18 0.49 401494 liEl6uEi4h3N0AiCFc PTPLAD2 8.13 2.6 0.020.06 −4.31 0.01 2.05 64746 ZVJ0yu9Me8TUgT_0p0 ACBD3 7.76 5.39 0 0 0.510.63 2.05 7168 cIjQrX9YQngop4h2p4 TPM1 8.69 3.38 0.01 0.02 −2.92 0.052.05 29766 l1KiIq623uT1K8eR_0 TMOD3 7.74 12.6 0 0 8.82 1 2.05 26656cFAVSEyotP6ICXs7o GDI2 7.85 7.84 0 0 3.99 0.98 2.05 29887lsC9OU1KT8ImNdNX0k SNX10 7.85 4.36 0 0.01 −1.19 0.23 2.05 10097ckvq9KgOo_H6X0p1.o ACTR2 7.76 8.82 0 0 5.17 0.99 2.05 4609xTXtbUJIokAnT94Ioc MYC 7.61 10.63 0 0 7.07 1 2.05 NekQ0sOQFKr089cU108.09 −4.37 0 0.01 −1.18 0.23 0.49 7913 3ei_qd_n9Iv68NLvj0 DEK 7.97 2.550.03 0.06 −4.39 0.01 2.05 HeLKWh27p0Zew1SOe8 8.43 2.38 0.04 0.08 −4.680.01 2.05 ZrXUBVXCAVoPMV6oGo 8.63 −5.36 0 0 0.46 0.61 0.49 92935fV_BS7XIUjj.5U7s1U MARS2 7.73 7.09 0 0 3.01 0.95 2.05 55664TkO.EIHr496ik3nEt0 CDC37L1 7.7 7.67 0 0 3.77 0.98 2.05 10985KV7SOAOPRJ3pL1Qt6o GCN1L1 8.64 −9.39 0 0 5.8 1 0.49 9opK4kt6gT9AIoCqaI8.77 −5.79 0 0 1.14 0.76 0.49 55142 QLTjRlHmcSXqYRLCFc CEP27 8.28 2.310.04 0.09 −4.81 0.01 2.04 595 3aZ9UkUE7BaTv1JIIQ CCND1 7.93 2.26 0.050.09 −4.89 0.01 2.04 BZ4_BIwMYB5TTT_yA 7.58 7.71 0 0 3.83 0.98 2.0485403 06QoKyj94B0pfBQyvo EAF1 8.17 3.26 0.01 0.03 −3.14 0.04 2.04 284418cHuKBGlFCkiiMSig2o FAM71E2 8.88 −4.1 0 0.01 −1.64 0.16 0.49 282809roortRPzruzKwTqgDk WDR51B 7.44 9.32 0 0 5.71 1 2.04 6noAkCKVCgSRIV4euo8.46 −5.11 0 0 0.06 0.52 0.49 26225 9d7vd7PscFBdUDZ4nk ARL5A 7.48 6.93 00 2.8 0.94 2.04 6KES0BTJFBzeX.Ueqo 8.49 −5.94 0 0 1.37 0.8 0.49fn4ygnHqVzgaKHC6Co 8.66 −5.36 0 0 0.47 0.62 0.49 2538273oLk6h.V3eR1J3x7FM MSRB3 7.77 3.48 0.01 0.02 −2.73 0.06 2.04 10472f6oKq8shzuj5pJIp5I ZNF238 7.36 9.75 0 0 6.18 1 2.04 6434QStf58UCilQ.R0Dv_I SFRS10 8.02 4.3 0 0.01 −1.3 0.21 2.04 64924ETkvnq7PP0d_6..pdE SLC30A5 7.98 6 0 0 1.45 0.81 2.04 79230TZHS0N9EKRCIvTGqio ZNF557 8.64 −5.18 0 0 0.17 0.54 0.49 9516rkT.iTt6sU65o5_oFI LITAF 7.68 8.32 0 0 4.58 0.99 2.04 23387ikV1JBBI4CUuJccFuU KIAA0999 7.36 9 0 0 5.36 1 2.04 iuVLv_O74jhyOzpPuo9.23 −2.82 0.02 0.04 −3.92 0.02 0.49 3eqMsORAOuieCKqOqY 8.47 −5.35 0 00.45 0.61 0.49 Ts.vi6de5le570K56o 8.69 −5 0 0 −0.12 0.47 0.49 1131156XS.03dSUW7.XVsQUo FAM54A 7.72 11.66 0 0 8.02 1 2.04 23345usS.nAlC.7_z4.f5Pw SYNE1 7.51 5.96 0 0 1.4 0.8 2.04 8543KcV08EPJKkelIv7Fe4 LMO4 7.78 10.15 0 0 6.59 1 2.04 6921fmunmoeGIBxwL16oJA TCEB1 7.55 7.28 0 0 3.26 0.96 2.04 24139iWrqCKi0TZ.qjU_u.o EML2 7.71 5.51 0 0 0.7 0.67 2.04 116985oIvY4d4cY4rVIoqlqo CENTD2 8.77 −5.5 0 0 0.7 0.67 0.49 15333995SDsvlNI.j7gQoeHk TMEM167 7.65 8.41 0 0 4.68 0.99 2.04TSATTUttFVDl0FSoSo 8.65 −4.67 0 0 −0.66 0.34 0.49 518023TB3J5Vv37ggMgxWlE ACCN5 7.97 −6.07 0 0 1.56 0.83 0.49 55328H76Qo7ojPo9X7kuWuo C10orf59 8.62 −4.32 0 0.01 −1.26 0.22 0.49 7763f7H6uyh3Lvfq7Pk6nk ZFAND5 7.98 2.42 0.03 0.08 −4.62 0.01 2.039..STABB9Ioh6o.QJ0 7.98 −7.37 0 0 3.38 0.97 0.49 owq4IDNdU7RBb6ipqo 8.23−7.04 0 0 2.94 0.95 0.49 8939 oudu78lxv.dOXU8Uvk FUBP3 7.75 4.01 0 0.01−1.8 0.14 2.03 frx_4TjExSfrLoe6qI 8.58 −5.15 0 0 0.13 0.53 0.49 83889xEK7hUIrjSEQoLjlCo WDR87 8.16 −7.28 0 0 3.26 0.96 0.49 57149EVeQqyLSuItX64tP7E LYRM1 7.37 12.1 0 0 8.41 1 2.03 ulSctRNoko6BUj70K08.04 −6.26 0 0 1.84 0.86 0.49 55364 EjfXlCv_g8Su4lFOXo IMPACT 8.11 2.490.03 0.07 −4.5 0.01 2.03 900 6nngsu.KNdTpLy4Owg CCNG1 8.08 4.76 0 0−0.52 0.37 2.03 xupWoEp4p4rpdfgbqM 7.57 4.81 0 0 −0.44 0.39 2.03 904106rpuwoOSVXghJHELeo IFT20 8.42 9.05 0 0 5.42 1 2.03 200105Vyh979FIkoNC64pE ELF5 8.08 −5.42 0 0 0.56 0.64 0.49 1346373K09J9eLFE9VJx8hGo ADAT2 8.4 −4.63 0 0 −0.73 0.33 0.49 2618xU75QpS3gNep0LjXXk GART 8.85 2.76 0.02 0.05 −4.03 0.02 2.03 9536N5VZ4Z9X5b6f6O3_eQ PTGES 7.94 −8.04 0 0 4.24 0.99 0.49 54517r6EKf33NLJvxX_0Uuk PUS7 7.77 7.16 0 0 3.1 0.96 2.02 Qfp0P1XXg4Ibc91A9I7.47 7.16 0 0 3.1 0.96 2.02 uFd5haKHOVcdWgldoQ 7.66 9.13 0 0 5.51 1 2.021350 f64rllP03tdPd5l.ZI COX7C 7.54 7.23 0 0 3.2 0.96 2.02 60490cKn7ebP6J4p4p6fXlc PPCDC 7.66 5.83 0 0 1.2 0.77 2.02 22856EEbT6Knmz_wMl450.o CHSY1 8.33 2.52 0.03 0.07 −4.44 0.01 2.02 10096lgiwIQi76FLPkvey7Q ACTR3 8.05 5.27 0 0 0.32 0.58 2.02 643236c_BcCiVd8B_WgJpBao KSP37 8.68 −4.64 0 0 −0.72 0.33 0.49fhr7fOJR1ejoKj_KOo 8.86 −4.42 0 0.01 −1.09 0.25 0.5 6502fLhCJ6ryjWvod4TaOU SKP2 7.71 4.88 0 0 −0.31 0.42 2.02 5203Huik7on8xASpIFEggY PFDN4 7.71 5.47 0 0 0.65 0.66 2.02 85623t7554CO3u5ezQTuH0 DENR 8.01 2.6 0.02 0.06 −4.32 0.01 2.02 923126nf.tcgFWcv6jrJt6o MEX3A 8.65 −5.43 0 0 0.58 0.64 0.5 10724BRK4e4BI5V635.TR3I MGEA5 7.87 5.04 0 0 −0.05 0.49 2.02 58533WVKkr_fhd5dL3YdwKE SNX6 7.63 13.09 0 0 9.21 1 2.02 5884u4QWXbpXaWl3gipLio RAD17 8.62 −4.02 0 0.01 −1.79 0.14 0.5 81537HKhb9Uw.qXOc174.84 SGPP1 7.84 3.17 0.01 0.03 −3.29 0.04 2.02 283489B1x16l8Ttl76p8IUr4 ZNF828 7.8 6.68 0 0 2.44 0.92 2.02 uskAm6rAV61UCCruPo8.05 −5.92 0 0 1.33 0.79 0.5 olR2eToSCeXP0Lyu9M 8.17 −5.72 0 0 1.03 0.740.5 2355 iJJIOJSiySiOpAgB6o FOSL2 8.74 −5.15 0 0 0.14 0.53 0.5 79022cO6p_PRX01Pp6BOj6o TMEM106C 8.28 3.12 0.01 0.03 −3.38 0.03 2.01 221710NlPiS10ivOh3QmHDoM LOC221710 7.77 6.48 0 0 2.16 0.9 2.01Tv1RK96KJUo6PPiJOo 8.33 −5.64 0 0 0.9 0.71 0.5 2530 QiF7uBz4gjaBJ18d4oFUT8 7.52 5.07 0 0 0 0.5 2.01 7546 fluUC3V9799JE_FTJE ZIC2 7.47 10.48 00 6.92 1 2.01 5985 BAZH7.TkomqQsK_JeE RFC5 7.8 9.21 0 0 5.59 1 2.01196527 6V6oD46u6S6F7giog0 TMEM16F 7.49 7.42 0 0 3.45 0.97 2.01lARX13TEiIRAR8OUeo 8.72 −3.9 0 0.01 −1.99 0.12 0.5 ovdKUjvouKi5_zSgCo8.64 −3.99 0 0.01 −1.83 0.14 0.5 6202 oA0kt16KJL1JKkJ9_Y RPS8 9.06 6.930 0 2.8 0.94 2.01 51444 f.Vd._0uT6gyoyH8SM RNF138 7.66 7.15 0 0 3.090.96 2.01 cSCXKEiRMqCME9QRKo 8.53 −4.46 0 0.01 −1.02 0.26 0.5 25988cq3llSjosQ67jfp3_Q MIZF 7.9 2.99 0.01 0.04 −3.62 0.03 2.010RHfQRhfYh4oJS0U4o 7.96 −6.56 0 0 2.27 0.91 0.5 1248016mnkdUI6addamLH0m8 LSM12 7.47 4.57 0 0 −0.83 0.3 2.01 QKV00jqdXjfoddJf6E7.45 11.15 0 0 7.56 1 2 6170 ldd9f3WU267vfh1nnY RPL39 7.49 6.48 0 0 2.160.9 2 ZUwgqdQJBKCU66Irio 8.58 −5.39 0 0 0.51 0.62 0.5 57708c_Rx.9Lr361X8UTfq4 MIER1 7.6 6.36 0 0 1.99 0.88 2 94234r5KQanEn88uvdwe63U FOXQ1 7.88 3.07 0.01 0.03 −3.47 0.03 2 5504Zk5Qkk50uq.yntE5J4 PPP1R2 7.78 8.23 0 0 4.46 0.99 2 1810QHzs9FCVADI_6dUo9Q DR1 7.46 10.25 0 0 6.69 1 2 BCDF50nUiEbAqEiPqo 8.53−4.32 0 0.01 −1.25 0.22 0.5 54948 c56kxoCx4lTOH4VEKo MRPL16 8.59 −5.05 00 −0.03 0.49 0.5

While the preferred embodiments of the invention have been illustratedand described in detail, it will be appreciated by those skilled in theart that that various changes can be made therein without departing fromthe spirit and scope of the invention. Accordingly, the particulararrangements disclosed are meant to be illustrative only and notlimiting as to the scope of the invention, which is to be given the fullbreadth of the appended claims and any equivalent thereof.

All references, patents, or applications cited herein are incorporatedby reference in their entirety, as if written herein.

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1. An HuR-associated biomarker selected from the group consisting ofCALM2, CD9, SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1,wherein the level of expression of the HuR-associated biomarker is over-or under-expressed in a breast cancer sample compared to a standardlevel of expression of the same biomarker in a non-cancerous sample. 2.A set of HuR-associated biomarkers comprising at least one biomarkerselected from the group consisting of CALM2, CD9, SRRM1, CCN1, DAZAP2,ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, wherein the level of expression atleast one biomarker is over- or under-expressed in a breast cancersample compared to a standard level of expression of the same biomarkerin a non-cancerous sample.
 3. The set of claim 2, wherein said standardlevel of expression is the median expression level of the biomarker in anon-cancerous sample obtained from one or more samples obtained from apopulation of healthy subjects.
 4. The set of claim 2, wherein saidstandard level of expression is the median expression level of thebiomarker in a non-cancerous sample obtained from one or more samplesobtained from a subject having breast cancer.
 5. The set of claim 2,wherein the ratio of expression of at least one biomarker expressed inthe breast cancer sample compared to the non-cancerous sample is lessthan ½ or greater than
 2. 6. The set of claim 2, wherein said breastcancer is an estrogen receptor positive breast cancer.
 7. The set ofclaim 2, wherein said breast cancer is an estrogen receptor negativebreast cancer.
 8. The set of claim 2, wherein at least one of saidbiomarkers is an mRNA.
 9. The set of claim 2, wherein at least one ofsaid biomarkers is a polypeptide.
 10. The set of claim 2, wherein atleast one of said biomarkers is post-transcriptionally regulated. 11.The set of claim 2, further comprising at least one biomarker selectedfrom the group consisting of Prothymosin-α, Bcl-2, Mcl-1, SirT1, TGF-b,MMP-9, MTC-1, μPA, VEGF-α, HIF1-α and cyclins A1 (CCNA1), B1 and D1. 12.The set of claim 2, further comprising at least one biomarker selectedfrom the group consisting of Glut-1, ERα, COX-2, IL-8, Cyclin E1, BRCA-1and Thrombospondin
 1. 13. The set of claim 2, further comprising atleast one biomarker selected from the group consisting of CD9, PTMA,UBE2E2, CCNI, CKLF, SRRM1, STK4, FKBP1A, PMP22, CALM2, MMD, CSDA, CHIC2,DAZAP2, ZNF22, ATP1B1, TRAM1, ENY2, ALKBH5, RAP2A, TMCO1, and ARL6IP1.14. The set of claim 2, further comprising at least one biomarkerselected from the group consisting of ACTB, SMNDC1, MAL2, CALM2,CDK2AP1, hCG_(—)1781062, JUND, ARL6IP1, PTMA, ATP6V1G1, ACTB, HMGB1,BUB3, PJA2, LOC203547, NPM1, MATR3, TMC01, CXCR7, ZFP36L1, SFRS2, TMSL3,PLOD2, PPP6C, EIF4A2, RPS6KB1, HSPA1A, TIMEM59, FOXA1, PEX11B, MYB, CD9,ZNF14, ITGB1, PARD6B, LOC441087, SRRM1, SNX16, PUM1, MORF4L1, TFDP1,MMD, GCA, CISD2, C4orf34, DAZAP2, G3BP1, C21orf55, NCOA3, ATP1B1, SFPQ,PRKAR1A, YBX1, HIST1H3E, CCNI, CSTB, C15orf51, YWHAZ, PRIM2, SLC7A1,C15orf15, PCBP2, ROD1, SPINT2, CALMG, and YTHDC1.
 15. A kit formeasuring the level of expression of a set of HuR-associated biomarkerscomprising at least one biomarker selected from the group consisting ofCALM2, CD9, SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1,wherein the level of expression at least one biomarker is over- orunder-expressed in a breast cancer sample compared to a standard levelof expression of the same biomarker in a non-cancerous sample.
 16. Amethod for aiding in the diagnosis of breast cancer in a subjectcomprising: (a) obtaining a sample from said subject; (b) measuring thelevel of expression of a set of HuR-associated biomarkers comprising atleast one biomarker selected from the group consisting of CALM2, CD9,SRRM1, CCN1, DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, in saidsample obtained from the subject; and (c) comparing the level ofexpression of each biomarker in the set of HuR-associated biomarkers tothe standard level of expression of the same biomarker in anon-cancerous sample; wherein a significant difference in the ratio ofexpression of at least one biomarker in the set aids in the diagnosis ofbreast cancer.
 17. The method of claim 16, wherein said standard levelof expression is the median expression level of the biomarker in anon-cancerous sample obtained from one or more samples obtained from apopulation of healthy subjects.
 18. The method of claim 16, wherein saidstandard level of expression is the median expression level of thebiomarker in a non-cancerous sample obtained from one or more samplesobtained from a subject having breast cancer.
 19. A method formonitoring the disease status of breast cancer in a subject comprising:(a) obtaining a sample from said subject; (b) measuring the level ofexpression of a set of HuR-associated biomarkers comprising at least onebiomarker selected from the group consisting of CALM2, CD9, SRRM1, CCN1,DAZAP2, ARL6IP1, PTMA, ATP1B1, MMD and TMCO1, in said sample obtainedfrom the subject; and (c) comparing the level of expression of eachbiomarker in the set of HuR-associated biomarkers to the standard levelof expression of the same biomarker in a non-cancerous sample; wherein asignificant difference in the ratio of expression of at least onebiomarker in the set aids in monitoring the disease status of breastcancer.
 20. The method of claim 19, wherein the ratio of expression ofat least one biomarker expressed in the cancer sample compared to thenon-cancerous sample is less than ½ or greater than 2.